Your first neural network

In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementation of the neural network up to you (for the most part). After you've submitted this project, feel free to explore the data and the model more.

%matplotlib inline
%config InlineBackend.figure_format = 'retina'

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

Load and prepare the data

A critical step in working with neural networks is preparing the data correctly. Variables on different scales make it difficult for the network to efficiently learn the correct weights. Below, we've written the code to load and prepare the data. You'll learn more about this soon!

data_path = 'Bike-Sharing-Dataset/hour.csv'

rides = pd.read_csv(data_path)

rides.head()

	instant	dteday	season	yr	mnth	hr	holiday	weekday	workingday	weathersit	temp	atemp	hum	windspeed	casual	registered	cnt
0	1	2011-01-01	1	0	1	0	0	6	0	1	0.24	0.2879	0.81	0.0	3	13	16
1	2	2011-01-01	1	0	1	1	0	6	0	1	0.22	0.2727	0.80	0.0	8	32	40
2	3	2011-01-01	1	0	1	2	0	6	0	1	0.22	0.2727	0.80	0.0	5	27	32
3	4	2011-01-01	1	0	1	3	0	6	0	1	0.24	0.2879	0.75	0.0	3	10	13
4	5	2011-01-01	1	0	1	4	0	6	0	1	0.24	0.2879	0.75	0.0	0	1	1

Checking out the data

This dataset has the number of riders for each hour of each day from January 1 2011 to December 31 2012. The number of riders is split between casual and registered, summed up in the cnt column. You can see the first few rows of the data above.

Below is a plot showing the number of bike riders over the first 10 days or so in the data set. (Some days don't have exactly 24 entries in the data set, so it's not exactly 10 days.) You can see the hourly rentals here. This data is pretty complicated! The weekends have lower over all ridership and there are spikes when people are biking to and from work during the week. Looking at the data above, we also have information about temperature, humidity, and windspeed, all of these likely affecting the number of riders. You'll be trying to capture all this with your model.

rides[:24*10].plot(x='dteday', y='cnt')

<matplotlib.axes._subplots.AxesSubplot at 0x1fd70ad46a0>

Dummy variables

Here we have some categorical variables like season, weather, month. To include these in our model, we'll need to make binary dummy variables. This is simple to do with Pandas thanks to get_dummies().

dummy_fields = ['season', 'weathersit', 'mnth', 'hr', 'weekday']
for each in dummy_fields:
    dummies = pd.get_dummies(rides[each], prefix=each, drop_first=False)
    rides = pd.concat([rides, dummies], axis=1)

fields_to_drop = ['instant', 'dteday', 'season', 'weathersit', 
                  'weekday', 'atemp', 'mnth', 'workingday', 'hr']
data = rides.drop(fields_to_drop, axis=1)
data.head()

	yr	holiday	temp	hum	windspeed	casual	registered	cnt	season_1	season_2	...	hr_21	hr_22	hr_23	weekday_0	weekday_1	weekday_2	weekday_3	weekday_4	weekday_5	weekday_6
0	0	0	0.24	0.81	0.0	3	13	16	1	0	...	0	0	0	0	0	0	0	0	0	1
1	0	0	0.22	0.80	0.0	8	32	40	1	0	...	0	0	0	0	0	0	0	0	0	1
2	0	0	0.22	0.80	0.0	5	27	32	1	0	...	0	0	0	0	0	0	0	0	0	1
3	0	0	0.24	0.75	0.0	3	10	13	1	0	...	0	0	0	0	0	0	0	0	0	1
4	0	0	0.24	0.75	0.0	0	1	1	1	0	...	0	0	0	0	0	0	0	0	0	1

5 rows × 59 columns

Scaling target variables

To make training the network easier, we'll standardize each of the continuous variables. That is, we'll shift and scale the variables such that they have zero mean and a standard deviation of 1.

The scaling factors are saved so we can go backwards when we use the network for predictions.

quant_features = ['casual', 'registered', 'cnt', 'temp', 'hum', 'windspeed']
# Store scalings in a dictionary so we can convert back later
scaled_features = {}
for each in quant_features:
    mean, std = data[each].mean(), data[each].std()
    scaled_features[each] = [mean, std]
    data.loc[:, each] = (data[each] - mean)/std

Splitting the data into training, testing, and validation sets

We'll save the data for the last approximately 21 days to use as a test set after we've trained the network. We'll use this set to make predictions and compare them with the actual number of riders.

# Save data for approximately the last 21 days 
test_data = data[-21*24:]

# Now remove the test data from the data set 
data = data[:-21*24]

# Separate the data into features and targets
target_fields = ['cnt', 'casual', 'registered']
features, targets = data.drop(target_fields, axis=1), data[target_fields]
test_features, test_targets = test_data.drop(target_fields, axis=1), test_data[target_fields]

We'll split the data into two sets, one for training and one for validating as the network is being trained. Since this is time series data, we'll train on historical data, then try to predict on future data (the validation set).

# Hold out the last 60 days or so of the remaining data as a validation set
train_features, train_targets = features[:-60*24], targets[:-60*24]
val_features, val_targets = features[-60*24:], targets[-60*24:]

%pdb

Automatic pdb calling has been turned ON

Time to build the network

Below you'll build your network. We've built out the structure and the backwards pass. You'll implement the forward pass through the network. You'll also set the hyperparameters: the learning rate, the number of hidden units, and the number of training passes.

The network has two layers, a hidden layer and an output layer. The hidden layer will use the sigmoid function for activations. The output layer has only one node and is used for the regression, the output of the node is the same as the input of the node. That is, the activation function is $f(x)=x$. A function that takes the input signal and generates an output signal, but takes into account the threshold, is called an activation function. We work through each layer of our network calculating the outputs for each neuron. All of the outputs from one layer become inputs to the neurons on the next layer. This process is called forward propagation.

We use the weights to propagate signals forward from the input to the output layers in a neural network. We use the weights to also propagate error backwards from the output back into the network to update our weights. This is called backpropagation.

Hint: You'll need the derivative of the output activation function ($f(x) = x$) for the backpropagation implementation. If you aren't familiar with calculus, this function is equivalent to the equation $y = x$. What is the slope of that equation? That is the derivative of $f(x)$.

Below, you have these tasks:

1. Implement the sigmoid function to use as the activation function. Set self.activation_function in __init__ to your sigmoid function.
2. Implement the forward pass in the train method.
3. Implement the backpropagation algorithm in the train method, including calculating the output error.
4. Implement the forward pass in the run method.

class NeuralNetwork(object):
    def __init__(self, input_nodes, hidden_nodes, output_nodes, learning_rate):
        # Set number of nodes in input, hidden and output layers.
        self.input_nodes = input_nodes
        self.hidden_nodes = hidden_nodes
        self.output_nodes = output_nodes

        # Initialize weights
        self.weights_input_to_hidden = np.random.normal(0.0, self.input_nodes**-0.5, 
                                       (self.input_nodes, self.hidden_nodes))

        self.weights_hidden_to_output = np.random.normal(0.0, self.hidden_nodes**-0.5, 
                                       (self.hidden_nodes, self.output_nodes))
        self.lr = learning_rate
        
        #### TODO: Set self.activation_function to your implemented sigmoid function ####
        #
        # Note: in Python, you can define a function with a lambda expression,
        # as shown below.
        #self.activation_function = lambda x : 0  # Replace 0 with your sigmoid calculation.
        
        ### If the lambda code above is not something you're familiar with,
        # You can uncomment out the following three lines and put your 
        # implementation there instead.
        #
        def sigmoid(x):
            return 1/(1+np.exp(-x))  # Replace 0 with your sigmoid calculation here
        self.activation_function = sigmoid
                    
    
    def train(self, features, targets):
        ''' Train the network on batch of features and targets. 
        
            Arguments
            ---------
            
            features: 2D array, each row is one data record, each column is a feature
            targets: 1D array of target values
        
        '''
        n_records = features.shape[0]
        delta_weights_i_h = np.zeros(self.weights_input_to_hidden.shape)
        delta_weights_h_o = np.zeros(self.weights_hidden_to_output.shape)
        for X, y in zip(features, targets):
            #### Implement the forward pass here ####
            ### Forward pass ###
            # TODO: Hidden layer - Replace these values with your calculations.
            hidden_inputs = np.dot(X, self.weights_input_to_hidden) # signals into hidden layer
            hidden_outputs = self.activation_function(hidden_inputs) # signals from hidden layer

            # TODO: Output layer - Replace these values with your calculations.
            final_inputs = np.dot(hidden_outputs, self.weights_hidden_to_output) # signals into final output layer
            final_outputs = final_inputs # signals from final output layer
            
            #### Implement the backward pass here ####
            ### Backward pass ###

            # TODO: Output error - Replace this value with your calculations.
            error = y - final_outputs # Output layer error is the difference between desired target and actual output.
            
            # I moved the output_error_term_here
            output_error_term = error
            
            # TODO: Hidden error - calculate the hidden layer's contribution to the error
            hidden_error = np.dot(self.weights_hidden_to_output, output_error_term)
            
            # TODO: Backpropagated error terms - Replace these values with your calculations
            hidden_error_term = hidden_error * hidden_outputs * (1 + (-hidden_outputs))

            # Weight step (input to hidden)
            delta_weights_i_h += hidden_error_term * X[:, None]
            # Weight step (hidden to output)
            delta_weights_h_o += output_error_term * hidden_outputs[:, None]

        # TODO: Update the weights - Replace these values with your calculations.
        self.weights_hidden_to_output += self.lr * delta_weights_h_o / n_records # update hidden-to-output weights with gradient descent step
        self.weights_input_to_hidden += self.lr * delta_weights_i_h / n_records # update input-to-hidden weights with gradient descent step
        
        print("hidden_inputs =", hidden_inputs)
        print("hidden_outputs =", hidden_outputs)
        print("final_inputs =", final_inputs)
        print("final_outputs =", final_outputs)
        print("error =", error)
        print("output_error_term =", output_error_term)
        print("hidden_error =", hidden_error)
        print("hidden_error_term =", hidden_error_term)
        print("delta_weights_i_h =", delta_weights_i_h)
        print("delta_weights_h_o =", delta_weights_h_o)
        print("self.weights_hidden_to_output =", self.weights_hidden_to_output)
        print("self.weights_input_to_hidden =", self.weights_input_to_hidden)
        
    def run(self, features):
        ''' Run a forward pass through the network with input features 
        
            Arguments
            ---------
            features: 1D array of feature values
        '''
        
        #### Implement the forward pass here ####
        # TODO: Hidden layer - replace these values with the appropriate calculations.
        hidden_inputs = np.dot(features, self.weights_input_to_hidden) # signals into hidden layer
        hidden_outputs = self.activation_function(hidden_inputs) # signals from hidden layer
        
        # TODO: Output layer - Replace these values with the appropriate calculations.
        final_inputs = np.dot(hidden_outputs, self.weights_hidden_to_output) # signals into final output layer
        final_outputs = final_inputs # signals from final output layer 
        
        return final_outputs

def MSE(y, Y):
    return np.mean((y-Y)**2)

Unit tests

Run these unit tests to check the correctness of your network implementation. This will help you be sure your network was implemented correctly befor you starting trying to train it. These tests must all be successful to pass the project.

import unittest
import pdb

inputs = np.array([[0.5, -0.2, 0.1]])
targets = np.array([[0.4]])
test_w_i_h = np.array([[0.1, -0.2],
                       [0.4, 0.5],
                       [-0.3, 0.2]])
test_w_h_o = np.array([[0.3],
                       [-0.1]])

class TestMethods(unittest.TestCase):
    
    ##########
    # Unit tests for data loading
    ##########
    
    def test_data_path(self):
        # Test that file path to dataset has been unaltered
        self.assertTrue(data_path.lower() == 'bike-sharing-dataset/hour.csv')
        
    def test_data_loaded(self):
        # Test that data frame loaded
        self.assertTrue(isinstance(rides, pd.DataFrame))
    
    ##########
    # Unit tests for network functionality
    ##########

    def test_activation(self):
        network = NeuralNetwork(3, 2, 1, 0.5)
        # Test that the activation function is a sigmoid
        self.assertTrue(np.all(network.activation_function(0.5) == 1/(1+np.exp(-0.5))))

    def test_train(self):
        # Test that weights are updated correctly on training
        network = NeuralNetwork(3, 2, 1, 0.5)
        network.weights_input_to_hidden = test_w_i_h.copy()
        network.weights_hidden_to_output = test_w_h_o.copy()
        
        network.train(inputs, targets)
        self.assertTrue(np.allclose(network.weights_hidden_to_output, 
                                    np.array([[ 0.37275328], 
                                              [-0.03172939]])))
        self.assertTrue(np.allclose(network.weights_input_to_hidden,
                                    np.array([[ 0.10562014, -0.20185996], 
                                              [0.39775194, 0.50074398], 
                                              [-0.29887597, 0.19962801]])))

    def test_run(self):
        # Test correctness of run method
        network = NeuralNetwork(3, 2, 1, 0.5)
        network.weights_input_to_hidden = test_w_i_h.copy()
        network.weights_hidden_to_output = test_w_h_o.copy()

        self.assertTrue(np.allclose(network.run(inputs), 0.09998924))

suite = unittest.TestLoader().loadTestsFromModule(TestMethods())
unittest.TextTestRunner().run(suite)

.....

hidden_inputs = [-0.06 -0.18]
hidden_outputs = [ 0.4850045   0.45512111]
final_inputs = [ 0.09998924]
final_outputs = [ 0.09998924]
error = [ 0.30001076]
output_error_term = [ 0.30001076]
hidden_error = [ 0.09000323 -0.03000108]
hidden_error_term = [ 0.02248057 -0.00743984]
delta_weights_i_h = [[ 0.01124028 -0.00371992]
 [-0.00449611  0.00148797]
 [ 0.00224806 -0.00074398]]
delta_weights_h_o = [[ 0.14550657]
 [ 0.13654123]]
self.weights_hidden_to_output = [[ 0.37275328]
 [-0.03172939]]
self.weights_input_to_hidden = [[ 0.10562014 -0.20185996]
 [ 0.39775194  0.50074398]
 [-0.29887597  0.19962801]]

----------------------------------------------------------------------
Ran 5 tests in 0.015s

OK

<unittest.runner.TextTestResult run=5 errors=0 failures=0>

Training the network

Here you'll set the hyperparameters for the network. The strategy here is to find hyperparameters such that the error on the training set is low, but you're not overfitting to the data. If you train the network too long or have too many hidden nodes, it can become overly specific to the training set and will fail to generalize to the validation set. That is, the loss on the validation set will start increasing as the training set loss drops.

You'll also be using a method know as Stochastic Gradient Descent (SGD) to train the network. The idea is that for each training pass, you grab a random sample of the data instead of using the whole data set. You use many more training passes than with normal gradient descent, but each pass is much faster. This ends up training the network more efficiently. You'll learn more about SGD later.

Choose the number of iterations

This is the number of batches of samples from the training data we'll use to train the network. The more iterations you use, the better the model will fit the data. However, if you use too many iterations, then the model with not generalize well to other data, this is called overfitting. You want to find a number here where the network has a low training loss, and the validation loss is at a minimum. As you start overfitting, you'll see the training loss continue to decrease while the validation loss starts to increase.

Choose the learning rate

This scales the size of weight updates. If this is too big, the weights tend to explode and the network fails to fit the data. A good choice to start at is 0.1. If the network has problems fitting the data, try reducing the learning rate. Note that the lower the learning rate, the smaller the steps are in the weight updates and the longer it takes for the neural network to converge.

Choose the number of hidden nodes

The more hidden nodes you have, the more accurate predictions the model will make. Try a few different numbers and see how it affects the performance. You can look at the losses dictionary for a metric of the network performance. If the number of hidden units is too low, then the model won't have enough space to learn and if it is too high there are too many options for the direction that the learning can take. The trick here is to find the right balance in number of hidden units you choose.

import sys

### Set the hyperparameters here ###
iterations = 20000
learning_rate = 0.6
hidden_nodes = 6
output_nodes = 1

N_i = train_features.shape[1]
network = NeuralNetwork(N_i, hidden_nodes, output_nodes, learning_rate)

losses = {'train':[], 'validation':[]}
for ii in range(iterations):
    # Go through a random batch of 128 records from the training data set
    batch = np.random.choice(train_features.index, size=128)
    X, y = train_features.ix[batch].values, train_targets.ix[batch]['cnt']
                             
    network.train(X, y)
    
    # Printing out the training progress
    train_loss = MSE(network.run(train_features).T, train_targets['cnt'].values)
    val_loss = MSE(network.run(val_features).T, val_targets['cnt'].values)
    sys.stdout.write("\rProgress: {:2.1f}".format(100 * ii/float(iterations)) \
                     + "% ... Training loss: " + str(train_loss)[:5] \
                     + " ... Validation loss: " + str(val_loss)[:5])
    sys.stdout.flush()
    
    losses['train'].append(train_loss)
    losses['validation'].append(val_loss)

hidden_inputs = [ 0.07531046 -0.05363855  0.29486358 -0.72962575 -0.23315393  0.09593506]
hidden_outputs = [ 0.51881872  0.48659358  0.5731864   0.32527686  0.44197414  0.52396539]
final_inputs = [-0.06988101]
final_outputs = [-0.06988101]
error = [-0.50051679]
output_error_term = [-0.50051679]
hidden_error = [ 0.25976862  0.02959466  0.19885929  0.18051518 -0.33904186 -0.26156287]
hidden_error_term = [ 0.06485016  0.00739335  0.04864968  0.03961799 -0.08361891 -0.06524049]
delta_weights_i_h = [[ -1.65636154e+00  -1.81695195e-01  -1.25782546e+00  -1.13267188e+00
    1.91240233e+00   1.73373443e+00]
 [ -8.61681452e-02  -8.93520431e-03  -5.82554800e-02  -6.45353402e-02
    1.31367136e-01   9.94669383e-02]
 [ -5.19080766e+00  -5.78445515e-01  -3.97991787e+00  -3.59368251e+00
    6.36424159e+00   5.13305661e+00]
 [  2.99752826e+00   3.32931018e-01   2.33951264e+00   1.99681361e+00
   -3.34183532e+00  -2.88136460e+00]
 [ -7.86328718e-01  -9.36274570e-02  -6.69560425e-01  -6.57337260e-01
    8.72010465e-01   7.88184607e-01]
 [  1.12139941e+00   1.23139373e-01   8.62722472e-01   7.65649590e-01
   -1.46660600e+00  -1.08178534e+00]
 [ -1.53979704e-01  -1.45925889e-02  -1.08755899e-01  -7.54187949e-02
    1.07248664e-01   7.56492170e-02]
 [ -1.13873813e+00  -1.22713245e-01  -8.84489802e-01  -8.12458871e-01
    1.28460577e+00   1.16055482e+00]
 [ -1.53139353e-01  -1.65649447e-02  -6.82910055e-02  -1.00385001e-01
    1.99889110e-01   1.80584311e-01]
 [  1.03023400e-01   1.97605884e-02   8.28081371e-02   6.46482203e-02
   -4.33352392e-01  -1.10703402e-01]
 [ -4.92102639e-01  -5.68674139e-02  -3.39848973e-01  -3.16438522e-01
    6.06942693e-01   5.00882915e-01]
 [  6.46214628e-02   6.37542001e-03   5.82266013e-02   2.91772244e-02
   -4.84527562e-02  -5.51765080e-02]
 [  0.00000000e+00   0.00000000e+00   0.00000000e+00   0.00000000e+00
    0.00000000e+00   0.00000000e+00]
 [  1.56491931e-01   1.68760499e-02   1.24475608e-01   1.13056660e-01
   -2.38028285e-01  -1.69331175e-01]
 [  4.83156692e-01   5.49369231e-02   3.78424625e-01   3.18563657e-01
   -5.98880904e-01  -4.47011068e-01]
 [ -1.26228685e-01  -1.70278812e-02  -1.11455063e-01  -7.60505121e-02
    1.17444918e-01   1.49838746e-01]
 [  5.41956197e-01   6.28182392e-02   4.18397917e-01   3.69486369e-01
   -6.94848098e-01  -5.49476683e-01]
 [ -4.16840031e-01  -4.75257336e-02  -3.09221917e-01  -2.74731039e-01
    5.38446516e-01   3.98746952e-01]
 [  4.78200485e-02   5.57731935e-03   3.97387760e-02   3.95836781e-02
   -1.10080929e-01  -1.04467858e-01]
 [ -1.33099880e+00  -1.46687126e-01  -1.04228808e+00  -9.46890798e-01
    1.55795789e+00   1.33830074e+00]
 [ -4.64823937e-02  -3.63597932e-03  -2.87169829e-02  -3.22208066e-02
    3.18127852e-02   5.83861143e-02]
 [  3.00225924e-01   3.45272496e-02   2.32979951e-01   2.07672020e-01
   -3.90057260e-01  -2.83728373e-01]
 [ -6.06579735e-01  -6.83375204e-02  -4.11198625e-01  -4.03493106e-01
    7.52296724e-01   6.09693339e-01]
 [  2.70292018e-01   3.10348818e-02   2.03991721e-01   1.80333780e-01
   -3.35031342e-01  -2.61312902e-01]
 [  4.02729052e-01   4.67121719e-02   3.06057839e-01   2.82077020e-01
   -5.05894470e-01  -4.04634826e-01]
 [  1.91656073e-01   2.19291375e-02   1.46894986e-01   1.24789578e-01
   -2.33856881e-01  -1.75640320e-01]
 [  4.43416509e-01   5.07479014e-02   3.41936824e-01   2.98575885e-01
   -5.64095184e-01  -4.45310153e-01]
 [  4.41299892e-01   5.03510091e-02   3.45255453e-01   3.12773025e-01
   -5.67833668e-01  -4.36248954e-01]
 [  7.72113702e-01   8.94203196e-02   6.04775097e-01   5.33362308e-01
   -9.94240006e-01  -7.98870203e-01]
 [  2.53600342e-01   2.98836217e-02   1.99165193e-01   1.81795750e-01
   -3.42522044e-01  -2.66635308e-01]
 [  3.81255820e-01   4.44124626e-02   2.89945677e-01   2.67363001e-01
   -5.00480485e-01  -3.91299607e-01]
 [  4.04634773e-01   4.76233259e-02   3.14255770e-01   2.76396723e-01
   -5.07836305e-01  -4.00549655e-01]
 [ -1.27532144e-01  -1.44310297e-02  -9.50450979e-02  -8.67712911e-02
    1.53933807e-01   1.33175030e-01]
 [ -3.65398753e-01  -3.84323150e-02  -2.84409152e-01  -2.55810672e-01
    3.97116711e-01   3.68455943e-01]
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Progress: 0.0% ... Training loss: 0.893 ... Validation loss: 1.240hidden_inputs = [ 0.03402141 -0.02628575 -0.19199129 -0.21835197  0.77491101  0.43565457]
hidden_outputs = [ 0.50850453  0.49342894  0.45214907  0.44562786  0.68458228  0.60722312]
final_inputs = [ 0.17056362]
final_outputs = [ 0.17056362]
error = [ 0.12458837]
output_error_term = [ 0.12458837]
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hidden_error_term = [-0.01589039 -0.00201462 -0.0123311  -0.011051    0.01878784  0.01588207]
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Progress: 0.0% ... Training loss: 0.878 ... Validation loss: 1.261hidden_inputs = [ 0.11257967 -0.27554871  0.10935471 -0.4879389   0.17613633 -0.27908248]
hidden_outputs = [ 0.52811523  0.43154541  0.52731147  0.38037923  0.54392059  0.43067873]
final_inputs = [-0.10469332]
final_outputs = [-0.10469332]
error = [-0.88469674]
output_error_term = [-0.88469674]
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Progress: 0.0% ... Training loss: 0.868 ... Validation loss: 1.287hidden_inputs = [-0.45785291  0.12766979  0.48778579 -0.22729605  0.5850212   0.25737437]
hidden_outputs = [ 0.3874953   0.53187416  0.61958468  0.44341938  0.64222196  0.56399075]
final_inputs = [-0.02803015]
final_outputs = [-0.02803015]
error = [-0.92828157]
output_error_term = [-0.92828157]
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hidden_error_term = [ 0.12152107  0.02973019  0.10184023  0.09150045 -0.14427449 -0.11543058]
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Progress: 0.0% ... Training loss: 0.824 ... Validation loss: 1.207hidden_inputs = [-0.56000554  0.00939062 -0.26627784 -0.41719391  0.33651044  0.00395038]
hidden_outputs = [ 0.36354618  0.50234764  0.43382111  0.39718842  0.58334262  0.50098759]
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output_error_term = [ 1.46856273]
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Progress: 0.0% ... Training loss: 0.813 ... Validation loss: 1.212hidden_inputs = [-0.38392145 -0.2230662  -0.18028853 -0.24287103  0.53187873  0.34662342]
hidden_outputs = [ 0.40518144  0.44446354  0.45504956  0.43957895  0.62992119  0.58579853]
final_inputs = [ 0.14379291]
final_outputs = [ 0.14379291]
error = [-0.27865928]
output_error_term = [-0.27865928]
hidden_error = [ 0.14746733  0.03473687  0.12728788  0.10551288 -0.20516662 -0.15418997]
hidden_error_term = [ 0.03554102  0.00857708  0.03156478  0.02599302 -0.04782854 -0.03741244]
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delta_weights_h_o = [[ 0.87929673]
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self.weights_hidden_to_output = [[-0.52508131]
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Progress: 0.1% ... Training loss: 0.793 ... Validation loss: 1.183hidden_inputs = [-0.12412265 -0.15246176  0.39128665  0.0624824   0.3932786   0.64532019]
hidden_outputs = [ 0.46900912  0.46195822  0.5965924   0.51561552  0.59707171  0.6559551 ]
final_inputs = [ 0.06327079]
final_outputs = [ 0.06327079]
error = [ 0.68395181]
output_error_term = [ 0.68395181]
hidden_error = [-0.35913031 -0.08266108 -0.31455413 -0.25996003  0.52585701  0.39274214]
hidden_error_term = [-0.08943766 -0.02054564 -0.07570371 -0.06492662  0.12650915  0.08863326]
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self.weights_hidden_to_output = [[-0.54628176]
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Progress: 0.1% ... Training loss: 0.785 ... Validation loss: 1.200hidden_inputs = [-0.49196322 -0.42432874 -0.32846291  0.25956815  0.23002256  0.04129348]
hidden_outputs = [ 0.37943119  0.39548139  0.41861467  0.56453013  0.55725342  0.5103219 ]
final_inputs = [ 0.02379633]
final_outputs = [ 0.02379633]
error = [-0.09250603]
output_error_term = [-0.09250603]
hidden_error = [ 0.05053436  0.01326583  0.04422604  0.03724729 -0.07064063 -0.05251227]
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Progress: 0.1% ... Training loss: 0.765 ... Validation loss: 1.162hidden_inputs = [ 0.35472427  0.22359543  0.52405884 -0.08788097 -0.38075403 -0.21446069]
hidden_outputs = [ 0.58776273  0.55566713  0.62809637  0.47804389  0.40594505  0.44658938]
final_inputs = [-0.27928682]
final_outputs = [-0.27928682]
error = [-0.57227684]
output_error_term = [-0.57227684]
hidden_error = [ 0.30375386  0.07839896  0.26924113  0.22245837 -0.45661592 -0.3411698 ]
hidden_error_term = [ 0.07359886  0.01935679  0.06289239  0.05550735 -0.1101146  -0.0843192 ]
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Progress: 0.1% ... Training loss: 0.757 ... Validation loss: 1.109hidden_inputs = [ 0.07561911  0.7415719   0.01537231 -0.4760168   0.41611591  0.32485358]
hidden_outputs = [ 0.51889577  0.67733949  0.503843    0.38319314  0.60255345  0.58050665]
final_inputs = [ 0.18335436]
final_outputs = [ 0.18335436]
error = [-0.48912547]
output_error_term = [-0.48912547]
hidden_error = [ 0.24982642  0.05839365  0.21822716  0.18221917 -0.42177806 -0.31783103]
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Progress: 0.1% ... Training loss: 0.731 ... Validation loss: 1.143hidden_inputs = [-0.18756495 -0.54119512 -0.50798275 -0.41864178 -0.44443374 -0.51516191]
hidden_outputs = [ 0.45324575  0.36790961  0.37566654  0.39684181  0.39068501  0.37398423]
final_inputs = [-0.10261964]
final_outputs = [-0.10261964]
error = [-0.74343096]
output_error_term = [-0.74343096]
hidden_error = [ 0.41296669  0.12708669  0.36590075  0.31324778 -0.62658999 -0.46688695]
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Progress: 0.1% ... Training loss: 0.729 ... Validation loss: 1.071hidden_inputs = [-0.17976881 -0.24151103 -0.16359562  0.58690534  0.54922534 -0.13244588]
hidden_outputs = [ 0.45517844  0.43991402  0.45919207  0.64265477  0.63395585  0.46693685]
final_inputs = [ 0.14655972]
final_outputs = [ 0.14655972]
error = [-0.90991448]
output_error_term = [-0.90991448]
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hidden_error_term = [ 0.11831612  0.03278382  0.10633082  0.08271356 -0.19691023 -0.15949018]
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self.weights_hidden_to_output = [[-0.55809377]
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Progress: 0.1% ... Training loss: 0.699 ... Validation loss: 1.090hidden_inputs = [ 0.46540646  0.22665789  0.92546722  0.13405694 -0.69873228  0.13216812]
hidden_outputs = [ 0.61429595  0.55642312  0.71615478  0.53346413  0.33209336  0.53299402]
final_inputs = [-0.37038683]
final_outputs = [-0.37038683]
error = [ 0.26859879]
output_error_term = [ 0.26859879]
hidden_error = [-0.14990331 -0.05087739 -0.13652065 -0.1167472   0.24707273  0.18557066]
hidden_error_term = [-0.03551756 -0.01255738 -0.02775152 -0.02905606  0.05480255  0.04619065]
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Progress: 0.1% ... Training loss: 0.690 ... Validation loss: 1.104hidden_inputs = [-0.38379153  0.06997985 -0.74699916 -0.70283828  0.81814185  0.55195758]
hidden_outputs = [ 0.40521275  0.51748783  0.32147552  0.33118325  0.69384176  0.63458964]
final_inputs = [ 0.40670469]
final_outputs = [ 0.40670469]
error = [ 3.26795066]
output_error_term = [ 3.26795066]
hidden_error = [-1.87739768 -0.68630996 -1.72233671 -1.47175778  2.98235494  2.23265792]
hidden_error_term = [-0.45248171 -0.1713676  -0.3756916  -0.32599568  0.63352785  0.51772128]
delta_weights_i_h = [[-2.72051629 -1.01424566 -2.46047826 -1.92221572  2.96604651  2.83217852]
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Progress: 0.1% ... Training loss: 0.682 ... Validation loss: 1.067hidden_inputs = [-0.36571556 -0.64530961 -0.08906206 -0.62364676  0.62311116  0.21067114]
hidden_outputs = [ 0.4095767   0.34404728  0.47774919  0.34895251  0.6509258   0.55247385]
final_inputs = [ 0.30874005]
final_outputs = [ 0.30874005]
error = [-0.03564027]
output_error_term = [-0.03564027]
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Progress: 0.1% ... Training loss: 0.674 ... Validation loss: 1.107hidden_inputs = [ 0.2971301   0.95182893  0.68503512 -0.57983385  0.22368514  0.80386846]
hidden_outputs = [ 0.5737408   0.72148284  0.66486156  0.35897083  0.55568928  0.69080137]
final_inputs = [-0.07646621]
final_outputs = [-0.07646621]
error = [-0.53803604]
output_error_term = [-0.53803604]
hidden_error = [ 0.32587397  0.13175337  0.306147    0.26639409 -0.50682212 -0.37408853]
hidden_error_term = [ 0.07969649  0.02647523  0.06821588  0.06130015 -0.12513373 -0.07990338]
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Progress: 0.1% ... Training loss: 0.668 ... Validation loss: 1.106hidden_inputs = [-0.28559805  0.18357757  0.04140297  0.12385051 -0.47427732 -0.33915303]
hidden_outputs = [ 0.42908188  0.54576593  0.51034926  0.53092311  0.38360436  0.41601523]
final_inputs = [-0.30707897]
final_outputs = [-0.30707897]
error = [ 0.41478707]
output_error_term = [ 0.41478707]
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Progress: 0.2% ... Training loss: 0.664 ... Validation loss: 1.054hidden_inputs = [-0.30698081  0.13892111  0.61791072 -0.16616346  0.39993026  0.20056781]
hidden_outputs = [ 0.42385186  0.53467453  0.64974323  0.45855445  0.59867091  0.54997453]
final_inputs = [ 0.05030254]
final_outputs = [ 0.05030254]
error = [-1.07277093]
output_error_term = [-1.07277093]
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Progress: 0.2% ... Training loss: 0.677 ... Validation loss: 1.154hidden_inputs = [ 0.507933    0.7712382   0.33393016 -0.12336164 -0.96923169 -0.47885301]
hidden_outputs = [ 0.6243218   0.68378868  0.58271534  0.46919864  0.27503367  0.38252301]
final_inputs = [-0.67492766]
final_outputs = [-0.67492766]
error = [ 0.18171264]
output_error_term = [ 0.18171264]
hidden_error = [-0.1153571  -0.0507823  -0.11025172 -0.09868133  0.16962919  0.12546749]
hidden_error_term = [-0.02705633 -0.01098024 -0.02680861 -0.02457671  0.03382239  0.02963532]
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self.weights_hidden_to_output = [[-0.59844809]
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Progress: 0.2% ... Training loss: 0.652 ... Validation loss: 1.056hidden_inputs = [-0.73670628 -0.07478373  0.05378476 -0.13788036  0.10161317  0.20862708]
hidden_outputs = [ 0.32372481  0.48131278  0.51344295  0.46558441  0.52538146  0.55196841]
final_inputs = [ 0.09650398]
final_outputs = [ 0.09650398]
error = [ 0.38057887]
output_error_term = [ 0.38057887]
hidden_error = [-0.2277567  -0.09350278 -0.22043574 -0.19317151  0.38113801  0.28686048]
hidden_error_term = [-0.0498621  -0.02334304 -0.0550691  -0.04806408  0.09503897  0.07094039]
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Progress: 0.2% ... Training loss: 0.647 ... Validation loss: 1.033hidden_inputs = [-0.1058618  -0.45404271 -0.27647305  0.30814851 -0.51583786 -0.55107344]
hidden_outputs = [ 0.47355924  0.38840001  0.43131867  0.57643327  0.373826    0.3656154 ]
final_inputs = [-0.25197255]
final_outputs = [-0.25197255]
error = [-0.16405968]
output_error_term = [-0.16405968]
hidden_error = [ 0.09854573  0.03996025  0.09526633  0.08389715 -0.16948384 -0.12839462]
hidden_error_term = [ 0.02456754  0.00949238  0.0233672   0.02048416 -0.0396728  -0.02977995]
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delta_weights_h_o = [[-6.75783421]
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self.weights_hidden_to_output = [[-0.63234732]
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Progress: 0.2% ... Training loss: 0.646 ... Validation loss: 1.086hidden_inputs = [ 0.10811045  0.07994487  0.58133596 -0.25551645 -0.12551279  0.47130101]
hidden_outputs = [ 0.52700132  0.51997558  0.64137475  0.43646618  0.46866293  0.61569164]
final_inputs = [-0.17643969]
final_outputs = [-0.17643969]
error = [ 0.206965]
output_error_term = [ 0.206965]
hidden_error = [-0.13087376 -0.05893611 -0.1265336  -0.11189168  0.20855999  0.15486194]
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Progress: 0.2% ... Training loss: 0.641 ... Validation loss: 1.004hidden_inputs = [ 0.65662518  0.57601472  1.14249257  0.65387823 -0.78329098 -0.82439806]
hidden_outputs = [ 0.65850187  0.64014988  0.75813698  0.65788388  0.31361104  0.30483087]
final_inputs = [-0.75951513]
final_outputs = [-0.75951513]
error = [-0.13063992]
output_error_term = [-0.13063992]
hidden_error = [ 0.07940759  0.03375226  0.07686826  0.06731991 -0.1425368  -0.10674049]
hidden_error_term = [ 0.01785695  0.0077751   0.01409497  0.01515187 -0.03068235 -0.02261927]
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delta_weights_h_o = [[-2.80085431]
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self.weights_hidden_to_output = [[-0.62096454]
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Progress: 0.2% ... Training loss: 0.634 ... Validation loss: 0.999hidden_inputs = [-0.4300714  -0.61525722 -0.83535212 -0.49082443  1.3536617   0.52947388]
hidden_outputs = [ 0.39410928  0.35086089  0.30251458  0.37969937  0.79472763  0.6293604 ]
final_inputs = [ 0.67933607]
final_outputs = [ 0.67933607]
error = [-1.48679528]
output_error_term = [-1.48679528]
hidden_error = [ 0.92324715  0.39669375  0.8958522   0.79680516 -1.64461976 -1.23873107]
hidden_error_term = [ 0.22045956  0.09034999  0.18902438  0.18766973 -0.26829607 -0.2889537 ]
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Progress: 0.2% ... Training loss: 0.636 ... Validation loss: 1.076hidden_inputs = [ 0.41093358  0.78604066  0.56861341  0.61299311 -1.00090396 -0.50366381]
hidden_outputs = [ 0.60131171  0.68698055  0.63844316  0.64862327  0.26876373  0.37668005]
final_inputs = [-0.82106012]
final_outputs = [-0.82106012]
error = [ 0.04667924]
output_error_term = [ 0.04667924]
hidden_error = [-0.03077319 -0.01475209 -0.03000519 -0.02701711  0.04907375  0.03664516]
hidden_error_term = [-0.00737744 -0.00317226 -0.0069262  -0.0061575   0.00964445  0.008604  ]
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Progress: 0.2% ... Training loss: 0.625 ... Validation loss: 1.008hidden_inputs = [ -5.06502411e-01   3.99506120e-01   4.66414815e-01   2.04175395e-01
  -3.70544130e-02  -4.51612938e-04]
hidden_outputs = [ 0.3760138   0.59856899  0.61453484  0.55086726  0.49073746  0.4998871 ]
final_inputs = [-0.13723741]
final_outputs = [-0.13723741]
error = [-0.5323954]
output_error_term = [-0.5323954]
hidden_error = [ 0.33872875  0.15249843  0.32673425  0.29621093 -0.58520138 -0.44483084]
hidden_error_term = [ 0.07947505  0.03664296  0.07739739  0.07328629 -0.14625014 -0.1112077 ]
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    1.51548278e-01  -8.06625105e-02]
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Progress: 0.2% ... Training loss: 0.626 ... Validation loss: 0.987hidden_inputs = [-1.0731296  -0.22884336 -0.35049811 -0.37981007  0.56580027  0.57584692]
hidden_outputs = [ 0.25480838  0.44303753  0.41326164  0.40617271  0.63779354  0.64011122]
final_inputs = [ 0.50542548]
final_outputs = [ 0.50542548]
error = [ 0.22525794]
output_error_term = [ 0.22525794]
hidden_error = [-0.14187663 -0.06392627 -0.13759127 -0.12665     0.25416917  0.19452824]
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delta_weights_h_o = [[-6.68831198]
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self.weights_hidden_to_output = [[-0.66119221]
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Progress: 0.3% ... Training loss: 0.621 ... Validation loss: 1.034hidden_inputs = [-0.89863724  0.03867785  0.08891067 -0.2807366   1.06742026  0.52283353]
hidden_outputs = [ 0.28933063  0.50966826  0.52221304  0.4302732   0.74410601  0.6278101 ]
final_inputs = [ 0.3954952]
final_outputs = [ 0.3954952]
error = [-1.34629387]
output_error_term = [-1.34629387]
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Progress: 0.3% ... Training loss: 0.620 ... Validation loss: 1.036hidden_inputs = [-0.35828935 -0.2818316  -0.19010484 -0.83319564  1.04994273  0.87943627]
hidden_outputs = [ 0.41137373  0.43000479  0.45261641  0.30296979  0.7407639   0.70670539]
final_inputs = [ 0.5078191]
final_outputs = [ 0.5078191]
error = [-0.46075462]
output_error_term = [-0.46075462]
hidden_error = [ 0.30113683  0.14217086  0.29551095  0.27072655 -0.49720336 -0.37704353]
hidden_error_term = [ 0.07291889  0.03484617  0.07321425  0.05717179 -0.09547933 -0.0781509 ]
delta_weights_i_h = [[-0.77523912 -0.41473307 -0.70731593 -0.75393807  0.64224047  0.91308473]
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Progress: 0.3% ... Training loss: 0.615 ... Validation loss: 1.020hidden_inputs = [-0.2120645   0.24542975 -0.45116184  0.30229736  0.11949292 -0.48985111]
hidden_outputs = [ 0.44718167  0.56105129  0.38908456  0.57500403  0.52983774  0.37992864]
final_inputs = [-0.15321009]
final_outputs = [-0.15321009]
error = [-0.69284052]
output_error_term = [-0.69284052]
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Progress: 0.3% ... Training loss: 0.611 ... Validation loss: 0.996hidden_inputs = [ 0.03350362 -0.06379055  0.08170538  0.36797388 -0.59761513 -0.47693212]
hidden_outputs = [ 0.50837512  0.48405777  0.52041499  0.5909693   0.3548895   0.38297682]
final_inputs = [-0.42195923]
final_outputs = [-0.42195923]
error = [-0.57845694]
output_error_term = [-0.57845694]
hidden_error = [ 0.36900863  0.17396142  0.36317244  0.33469698 -0.63961846 -0.48963559]
hidden_error_term = [ 0.09222627  0.04344614  0.09064175  0.08090449 -0.14643613 -0.11570362]
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Progress: 0.3% ... Training loss: 0.616 ... Validation loss: 1.036hidden_inputs = [-0.11634307  0.63963095  0.75863951  0.31891015 -0.36027517 -0.19256256]
hidden_outputs = [ 0.470947    0.65467003  0.68105828  0.57905862  0.41089296  0.45200757]
final_inputs = [-0.51144879]
final_outputs = [-0.51144879]
error = [-0.46691516]
output_error_term = [-0.46691516]
hidden_error = [ 0.31170409  0.15350022  0.30786922  0.28619112 -0.50821264 -0.38729935]
hidden_error_term = [ 0.07766292  0.0347029   0.0668747   0.06975901 -0.12301792 -0.09593278]
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Progress: 0.3% ... Training loss: 0.608 ... Validation loss: 0.957hidden_inputs = [-0.33813324  0.37935004  0.45439345 -0.54835425  0.66432466  0.34859622]
hidden_outputs = [ 0.41626301  0.59371633  0.61168331  0.36624632  0.66023119  0.58627712]
final_inputs = [ 0.25719037]
final_outputs = [ 0.25719037]
error = [-0.25423035]
output_error_term = [-0.25423035]
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hidden_error_term = [ 0.03844659  0.01739711  0.03696165  0.03383462 -0.06502673 -0.05430331]
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Progress: 0.3% ... Training loss: 0.623 ... Validation loss: 1.052hidden_inputs = [ 0.93290377  1.00947646  0.7858424   0.31896037 -1.20335026 -0.40552433]
hidden_outputs = [ 0.71766403  0.73291768  0.68693792  0.57907087  0.23087976  0.39998579]
final_inputs = [-0.98803236]
final_outputs = [-0.98803236]
error = [ 0.19711232]
output_error_term = [ 0.19711232]
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Progress: 0.3% ... Training loss: 0.604 ... Validation loss: 0.990hidden_inputs = [ 0.17983333 -0.58425657 -0.06730964 -0.1713064   0.12822093  0.77336526]
hidden_outputs = [ 0.54483756  0.35795375  0.48317894  0.45727782  0.53201139  0.68424842]
final_inputs = [ 0.12708375]
final_outputs = [ 0.12708375]
error = [-0.26195013]
output_error_term = [-0.26195013]
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Progress: 0.3% ... Training loss: 0.602 ... Validation loss: 0.942hidden_inputs = [ 0.33563727  0.28826891  0.98832082  0.75508492 -1.18941551 -1.14823574]
hidden_outputs = [ 0.58313038  0.57157228  0.72875612  0.68028567  0.23336349  0.24081148]
final_inputs = [-0.90031454]
final_outputs = [-0.90031454]
error = [ 0.159012]
output_error_term = [ 0.159012]
hidden_error = [-0.10093241 -0.04493209 -0.09938758 -0.09382631  0.18495934  0.14315397]
hidden_error_term = [-0.02453559 -0.01100285 -0.01964601 -0.02040695  0.03309015  0.0261716 ]
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Progress: 0.3% ... Training loss: 0.610 ... Validation loss: 0.924hidden_inputs = [ 0.14359719 -0.12162439  0.8166402   0.19095338 -0.96366479 -0.69545218]
hidden_outputs = [ 0.53583774  0.46963133  0.69352268  0.54759381  0.27614504  0.33282131]
final_inputs = [-0.56115156]
final_outputs = [-0.56115156]
error = [-0.46682989]
output_error_term = [-0.46682989]
hidden_error = [ 0.29206893  0.12397368  0.28547118  0.26769497 -0.55644204 -0.43167699]
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delta_weights_h_o = [[-2.54925819]
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self.weights_hidden_to_output = [[-0.63759281]
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Progress: 0.4% ... Training loss: 0.615 ... Validation loss: 0.910hidden_inputs = [-0.49581772 -0.10938648  0.12886635 -0.75396853  0.99708977  1.03204264]
hidden_outputs = [ 0.37852402  0.47268062  0.53217208  0.31995719  0.73048601  0.73731171]
final_inputs = [ 0.71819224]
final_outputs = [ 0.71819224]
error = [-0.46163163]
output_error_term = [-0.46163163]
hidden_error = [ 0.29433301  0.1241315   0.28567761  0.26874063 -0.56816402 -0.44025641]
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Progress: 0.4% ... Training loss: 0.586 ... Validation loss: 0.933hidden_inputs = [ 0.18896002  0.22412719 -0.30841145 -0.63440398 -0.33257696 -0.0594907 ]
hidden_outputs = [ 0.54709994  0.55579842  0.42350253  0.34651262  0.41761374  0.48513171]
final_inputs = [-0.11259925]
final_outputs = [-0.11259925]
error = [ 0.46288181]
output_error_term = [ 0.46288181]
hidden_error = [-0.318627   -0.15005638 -0.31288594 -0.29121747  0.55637713  0.42600709]
hidden_error_term = [-0.07894991 -0.0370469  -0.07639052 -0.06594376  0.13531787  0.1064076 ]
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Progress: 0.4% ... Training loss: 0.585 ... Validation loss: 0.948hidden_inputs = [-0.17424327  0.03612449  0.30168822 -0.62091973  0.79071501  0.6404386 ]
hidden_outputs = [ 0.45654906  0.50903014  0.57485517  0.3495723   0.68798484  0.6548526 ]
final_inputs = [ 0.29556796]
final_outputs = [ 0.29556796]
error = [-0.70057408]
output_error_term = [-0.70057408]
hidden_error = [ 0.49203476  0.24054808  0.48354328  0.45209613 -0.83367187 -0.63618212]
hidden_error_term = [ 0.12207974  0.06011741  0.11817638  0.10279378 -0.17895742 -0.14379031]
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Progress: 0.4% ... Training loss: 0.580 ... Validation loss: 0.940hidden_inputs = [-0.9698837  -0.45860826 -1.18384454 -0.62136686  1.80997504  0.90875603]
hidden_outputs = [ 0.27490368  0.38731603  0.23436164  0.34947064  0.85935886  0.71274554]
final_inputs = [ 0.9534452]
final_outputs = [ 0.9534452]
error = [-0.63072792]
output_error_term = [-0.63072792]
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Progress: 0.4% ... Training loss: 0.576 ... Validation loss: 0.918hidden_inputs = [-0.85938353 -0.29962733  0.15550224 -0.40765704  0.19833478  0.43953346]
hidden_outputs = [ 0.29746816  0.42564859  0.53879741  0.39947405  0.54942179  0.60814786]
final_inputs = [ 0.2711602]
final_outputs = [ 0.2711602]
error = [-1.28811554]
output_error_term = [-1.28811554]
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hidden_error_term = [ 0.18379395  0.10512983  0.21450344  0.19372904 -0.38662969 -0.2835299 ]
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Progress: 0.4% ... Training loss: 0.609 ... Validation loss: 0.885hidden_inputs = [ 0.17849479  0.40231339  0.12316151  0.20676302 -1.06641941 -0.24179632]
hidden_outputs = [ 0.5445056   0.59924335  0.53075152  0.55150739  0.25608461  0.43984372]
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final_outputs = [-0.41029427]
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output_error_term = [-0.25382549]
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Progress: 0.4% ... Training loss: 0.569 ... Validation loss: 0.897hidden_inputs = [-1.15408085 -0.22352051 -0.42771276 -1.00128197  1.19642738  0.3973092 ]
hidden_outputs = [ 0.23974449  0.44435137  0.39467263  0.26868945  0.76788862  0.59804099]
final_inputs = [ 0.78178102]
final_outputs = [ 0.78178102]
error = [-0.83395155]
output_error_term = [-0.83395155]
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hidden_error_term = [ 0.10460911  0.06915142  0.13513563  0.10390405 -0.18586069 -0.19237773]
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Progress: 0.4% ... Training loss: 0.565 ... Validation loss: 0.897hidden_inputs = [-0.03541452 -0.05039897 -0.04774978 -0.50776897 -0.09465478 -0.28315198]
hidden_outputs = [ 0.4911473   0.48740292  0.48806482  0.37571668  0.47635396  0.4296812 ]
final_inputs = [-0.07312213]
final_outputs = [-0.07312213]
error = [-0.21059675]
output_error_term = [-0.21059675]
hidden_error = [ 0.14595673  0.07073086  0.14254144  0.1345833  -0.26188489 -0.20048852]
hidden_error_term = [ 0.03647774  0.01767149  0.03561506  0.031567   -0.06532479 -0.04913077]
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Progress: 0.4% ... Training loss: 0.562 ... Validation loss: 0.904hidden_inputs = [ 0.14051725 -0.33786302  0.07005078  0.08541085  0.34823764 -0.2179363 ]
hidden_outputs = [ 0.53507162  0.41632867  0.51750554  0.52133974  0.58619015  0.44573056]
final_inputs = [-0.07961149]
final_outputs = [-0.07961149]
error = [-0.76643912]
output_error_term = [-0.76643912]
hidden_error = [ 0.54229479  0.26328529  0.52903801  0.50066407 -0.94134689 -0.72184936]
hidden_error_term = [ 0.13490666  0.06397809  0.13209738  0.12493802 -0.2283437  -0.17833637]
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Progress: 0.5% ... Training loss: 0.563 ... Validation loss: 0.880hidden_inputs = [ 0.29778314 -0.16760618 -0.17747595 -0.33217586 -0.97790449 -0.3916322 ]
hidden_outputs = [ 0.5739005   0.45819627  0.45574711  0.4177113   0.27330778  0.40332444]
final_inputs = [-0.36132395]
final_outputs = [-0.36132395]
error = [-0.46818748]
output_error_term = [-0.46818748]
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Progress: 0.5% ... Training loss: 0.575 ... Validation loss: 0.938hidden_inputs = [ 0.05435307 -0.01834497  0.19742034  0.04116536  0.27257414 -0.02360525]
hidden_outputs = [ 0.51358492  0.49541389  0.54919541  0.51028989  0.56772474  0.49409896]
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Progress: 0.5% ... Training loss: 0.555 ... Validation loss: 0.903hidden_inputs = [ 0.5657692   0.88672923  0.87294577  0.6887224  -1.1802875  -0.95303296]
hidden_outputs = [ 0.63778637  0.70821474  0.70535828  0.66568266  0.23500051  0.27827528]
final_inputs = [-1.0894997]
final_outputs = [-1.0894997]
error = [ 0.05600519]
output_error_term = [ 0.05600519]
hidden_error = [-0.03969534 -0.02012295 -0.03931746 -0.03686857  0.0686762   0.0527808 ]
hidden_error_term = [-0.00917021 -0.00415834 -0.00817127 -0.00820507  0.01234628  0.0106004 ]
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Progress: 0.5% ... Training loss: 0.559 ... Validation loss: 0.872hidden_inputs = [ 0.64394793  0.4881932   1.11620639  0.52883239 -1.52803566 -0.4524698 ]
hidden_outputs = [ 0.65564535  0.6196807   0.75328436  0.62921074  0.17828127  0.38877371]
final_inputs = [-0.91224224]
final_outputs = [-0.91224224]
error = [-0.09920005]
output_error_term = [-0.09920005]
hidden_error = [ 0.06692923  0.03118011  0.06595178  0.06172645 -0.12738033 -0.09907803]
hidden_error_term = [ 0.01511092  0.00734842  0.01225694  0.01440106 -0.01866084 -0.02354379]
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delta_weights_h_o = [[-10.88744514]
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self.weights_hidden_to_output = [[-0.72572438]
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Progress: 0.5% ... Training loss: 0.549 ... Validation loss: 0.891hidden_inputs = [ 0.14268353 -0.35969827 -0.87200259  0.16722694  0.32128296  0.34776709]
hidden_outputs = [ 0.53561049  0.41103261  0.29483778  0.54170958  0.57963689  0.586076  ]
final_inputs = [ 0.17204366]
final_outputs = [ 0.17204366]
error = [ 0.09554306]
output_error_term = [ 0.09554306]
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Progress: 0.5% ... Training loss: 0.543 ... Validation loss: 0.875hidden_inputs = [ 0.37211342  0.68319875  0.44810502  1.09868935 -1.18559266 -0.86021665]
hidden_outputs = [ 0.59196956  0.66445225  0.61018859  0.75001445  0.23404811  0.29729408]
final_inputs = [-1.02162953]
final_outputs = [-1.02162953]
error = [ 0.17006587]
output_error_term = [ 0.17006587]
hidden_error = [-0.12307099 -0.06126129 -0.1224148  -0.11467515  0.21663106  0.16756875]
hidden_error_term = [-0.02972676 -0.01365854 -0.0291174  -0.02150076  0.03883536  0.03500684]
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Progress: 0.5% ... Training loss: 0.542 ... Validation loss: 0.854hidden_inputs = [ 0.27501159  0.82399054  0.54119129  0.41632577 -0.83829189 -0.75838395]
hidden_outputs = [ 0.56832283  0.69508276  0.6320895   0.60260371  0.30189465  0.31899723]
final_inputs = [-0.76793049]
final_outputs = [-0.76793049]
error = [ 0.07624546]
output_error_term = [ 0.07624546]
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hidden_error_term = [-0.01332549 -0.00561421 -0.01255389 -0.01209817  0.02114795  0.01702678]
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Progress: 0.5% ... Training loss: 0.540 ... Validation loss: 0.868hidden_inputs = [ 0.30713159  0.10076868  0.89645282  0.33828777 -1.45765913 -1.06227188]
hidden_outputs = [ 0.57618496  0.52517087  0.71022001  0.58377454  0.18882562  0.25687554]
final_inputs = [-1.04950506]
final_outputs = [-1.04950506]
error = [ 0.35782003]
output_error_term = [ 0.35782003]
hidden_error = [-0.26584505 -0.13446949 -0.2640085  -0.24654717  0.46307228  0.35913744]
hidden_error_term = [-0.06491826 -0.03353218 -0.05433494 -0.05990648  0.07092901  0.06855592]
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Progress: 0.5% ... Training loss: 0.545 ... Validation loss: 0.844hidden_inputs = [-0.2316061  -0.46316627 -0.63989168 -0.62601344  0.42786949  0.38024834]
hidden_outputs = [ 0.44235592  0.38623496  0.34527102  0.34841503  0.60536481  0.593933  ]
final_inputs = [ 0.52718152]
final_outputs = [ 0.52718152]
error = [ 0.14837134]
output_error_term = [ 0.14837134]
hidden_error = [-0.10586085 -0.05022705 -0.104573   -0.0986335   0.20083609  0.15715336]
hidden_error_term = [-0.02611345 -0.0119067  -0.02363966 -0.02239197  0.04797939  0.03790171]
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Progress: 0.5% ... Training loss: 0.540 ... Validation loss: 0.841hidden_inputs = [ 0.08694543 -0.05297251  0.05022579 -0.17580991 -0.00415952 -0.13666628]
hidden_outputs = [ 0.52172268  0.48675997  0.51255381  0.45616039  0.49896012  0.46588651]
final_inputs = [-0.03538988]
final_outputs = [-0.03538988]
error = [-0.45231208]
output_error_term = [-0.45231208]
hidden_error = [ 0.32558957  0.15377129  0.32197795  0.30324233 -0.61553433 -0.48282356]
hidden_error_term = [ 0.08124375  0.03841587  0.08044375  0.07522778 -0.15388292 -0.12014401]
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Progress: 0.6% ... Training loss: 0.537 ... Validation loss: 0.864hidden_inputs = [-0.36983883 -0.25660027 -0.13753497 -0.29620916  0.17568877  0.08058595]
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final_outputs = [ 0.08225452]
error = [ 1.02331672]
output_error_term = [ 1.02331672]
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Progress: 0.6% ... Training loss: 0.529 ... Validation loss: 0.852hidden_inputs = [ 0.27898417  0.44618892  0.59486513  0.12410862 -0.58758609 -0.56563666]
hidden_outputs = [ 0.56929716  0.60973273  0.64448065  0.53098739  0.35718891  0.36224425]
final_inputs = [-0.70563975]
final_outputs = [-0.70563975]
error = [-0.30580253]
output_error_term = [-0.30580253]
hidden_error = [ 0.2349846   0.11951821  0.23446745  0.21538287 -0.4010061  -0.31223187]
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Progress: 0.6% ... Training loss: 0.519 ... Validation loss: 0.836hidden_inputs = [-0.55293905 -0.2608941   0.32142988  0.27875706 -0.2033232  -0.31102926]
hidden_outputs = [ 0.3651828   0.43514393  0.57967268  0.56924148  0.44934359  0.42286353]
final_inputs = [-0.22969267]
final_outputs = [-0.22969267]
error = [-0.56674043]
output_error_term = [-0.56674043]
hidden_error = [ 0.42396081  0.21235511  0.4291761   0.38924794 -0.75294363 -0.58903036]
hidden_error_term = [ 0.09828443  0.05219555  0.10456973  0.09544578 -0.1863038  -0.14375284]
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delta_weights_h_o = [[-6.1059967 ]
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self.weights_hidden_to_output = [[-0.77669062]
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Progress: 0.6% ... Training loss: 0.536 ... Validation loss: 0.866hidden_inputs = [-0.08365325 -0.30406556  0.39820192  0.58505752 -0.97058505 -0.32627667]
hidden_outputs = [ 0.47909887  0.42456393  0.59825558  0.64223031  0.2747639   0.41914684]
final_inputs = [-0.70406471]
final_outputs = [-0.70406471]
error = [-0.18609034]
output_error_term = [-0.18609034]
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Progress: 0.6% ... Training loss: 0.521 ... Validation loss: 0.843hidden_inputs = [-0.86951728 -0.4202037  -0.40215465 -0.97751565  1.85207717  1.26308448]
hidden_outputs = [ 0.29535476  0.39646801  0.40079477  0.27338501  0.8643708   0.77955663]
final_inputs = [ 1.054121]
final_outputs = [ 1.054121]
error = [ 1.109957]
output_error_term = [ 1.109957]
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Progress: 0.6% ... Training loss: 0.516 ... Validation loss: 0.812hidden_inputs = [-1.25483392 -0.70901461 -1.36767219 -0.56346444  1.40111855  0.65366751]
hidden_outputs = [ 0.22186449  0.32981661  0.2029962   0.36274623  0.80236133  0.65783645]
final_inputs = [ 1.14579601]
final_outputs = [ 1.14579601]
error = [-0.82307873]
output_error_term = [-0.82307873]
hidden_error = [ 0.60529348  0.29346934  0.62221477  0.55779041 -1.13555861 -0.899433  ]
hidden_error_term = [ 0.10449825  0.06486776  0.10066735  0.12893961 -0.18007419 -0.20245127]
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Progress: 0.6% ... Training loss: 0.514 ... Validation loss: 0.808hidden_inputs = [-0.00676272  0.604323    0.6350808   0.51043276 -1.35235679 -0.24105131]
hidden_outputs = [ 0.49830933  0.64664472  0.65364062  0.62490792  0.20548533  0.44002729]
final_inputs = [-0.74263375]
final_outputs = [-0.74263375]
error = [-0.29637381]
output_error_term = [-0.29637381]
hidden_error = [ 0.21842878  0.10544285  0.22472909  0.20164212 -0.41468396 -0.32866214]
hidden_error_term = [ 0.05460657  0.0240932   0.05087744  0.04726451 -0.06770176 -0.08098343]
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delta_weights_h_o = [[ -8.65305146]
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self.weights_hidden_to_output = [[-0.77756551]
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Progress: 0.6% ... Training loss: 0.508 ... Validation loss: 0.825hidden_inputs = [ 0.50316027  0.38293983  0.79049059  0.25160277 -0.35106882 -0.13490918]
hidden_outputs = [ 0.62320172  0.59458196  0.68793666  0.56257096  0.41312326  0.46632377]
final_inputs = [-0.61946283]
final_outputs = [-0.61946283]
error = [-0.33684889]
output_error_term = [-0.33684889]
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Progress: 0.6% ... Training loss: 0.502 ... Validation loss: 0.809hidden_inputs = [-0.49263261 -0.08495225  0.43513205  0.42233561 -0.18486911 -0.29620941]
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Progress: 0.6% ... Training loss: 0.499 ... Validation loss: 0.809hidden_inputs = [-0.61312926 -0.43722621 -0.3713588  -0.58561189  0.90567255  0.7629862 ]
hidden_outputs = [ 0.3513457   0.39240211  0.40821273  0.35764232  0.71211382  0.68200172]
final_inputs = [ 0.71994852]
final_outputs = [ 0.71994852]
error = [-0.07196093]
output_error_term = [-0.07196093]
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hidden_error_term = [ 0.01263687  0.00667207  0.01374629  0.01153657 -0.02024765 -0.01689427]
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Progress: 0.7% ... Training loss: 0.497 ... Validation loss: 0.800hidden_inputs = [-0.16309723 -0.59068497 -0.88149316 -0.1792228   0.32453749  0.09077877]
hidden_outputs = [ 0.45931584  0.35647771  0.29286846  0.45531385  0.58042967  0.52267912]
final_inputs = [ 0.34287715]
final_outputs = [ 0.34287715]
error = [ 0.06804903]
output_error_term = [ 0.06804903]
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hidden_error_term = [-0.01303689 -0.00608417 -0.01115539 -0.01166062  0.0230857   0.01864418]
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Progress: 0.7% ... Training loss: 0.502 ... Validation loss: 0.820hidden_inputs = [ 0.29545213 -0.1822785  -0.07068615  0.16984639 -0.26799247 -0.33192567]
hidden_outputs = [ 0.57333038  0.45455613  0.48233582  0.54235981  0.43340001  0.41777215]
final_inputs = [-0.38862068]
final_outputs = [-0.38862068]
error = [-0.5235866]
output_error_term = [-0.5235866]
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Progress: 0.7% ... Training loss: 0.494 ... Validation loss: 0.804hidden_inputs = [-1.27089915 -0.51952754 -1.13277221 -1.00114809  1.71959118  1.67260883]
hidden_outputs = [ 0.21910337  0.37296272  0.24364986  0.26871575  0.84807617  0.84192334]
final_inputs = [ 1.39400343]
final_outputs = [ 1.39400343]
error = [ 1.48677185]
output_error_term = [ 1.48677185]
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hidden_error_term = [-0.19939618 -0.13909586 -0.22055746 -0.20711577  0.26527035  0.21790755]
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Progress: 0.7% ... Training loss: 0.493 ... Validation loss: 0.801hidden_inputs = [ 0.11798045  0.42275486 -0.13458526 -0.36156352  0.2548766   0.32731864]
hidden_outputs = [ 0.52946095  0.60414227  0.46640438  0.41058113  0.56337643  0.58110682]
final_inputs = [ 0.09795779]
final_outputs = [ 0.09795779]
error = [-0.17218055]
output_error_term = [-0.17218055]
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hidden_error_term = [ 0.03395423  0.01667109  0.0346509   0.02995853 -0.05912023 -0.04670788]
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Progress: 0.7% ... Training loss: 0.507 ... Validation loss: 0.773hidden_inputs = [-0.37179091 -0.03575566  0.10385949 -0.51974087  0.62155208  0.67573819]
hidden_outputs = [ 0.40810835  0.49106204  0.52594156  0.37291283  0.65057146  0.66278684]
final_inputs = [ 0.59856487]
final_outputs = [ 0.59856487]
error = [-0.63419623]
output_error_term = [-0.63419623]
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hidden_error_term = [ 0.11524206  0.05811941  0.12232094  0.10100354 -0.21260986 -0.168321  ]
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Progress: 0.7% ... Training loss: 0.492 ... Validation loss: 0.773hidden_inputs = [-0.51963829 -0.82202647 -0.48244267 -1.23055336  1.02842976  0.59937181]
hidden_outputs = [ 0.37293682  0.30533367  0.38167549  0.22608459  0.73661136  0.64551257]
final_inputs = [ 0.98589167]
final_outputs = [ 0.98589167]
error = [-0.55291327]
output_error_term = [-0.55291327]
hidden_error = [ 0.42163921  0.20768868  0.43219261  0.38218669 -0.81012919 -0.65124246]
hidden_error_term = [ 0.09860242  0.04405181  0.10199716  0.06687134 -0.15717727 -0.14902127]
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Progress: 0.7% ... Training loss: 0.479 ... Validation loss: 0.774hidden_inputs = [-0.43862906  0.04557141  0.06764972  0.25525348  0.56961792 -0.01604785]
hidden_outputs = [ 0.39206769  0.51139088  0.51690598  0.56346914  0.63867501  0.49598812]
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final_outputs = [ 0.15820696]
error = [ 0.63312008]
output_error_term = [ 0.63312008]
hidden_error = [-0.50483674 -0.25326847 -0.51648333 -0.45519577  0.91871889  0.73451892]
hidden_error_term = [-0.12032815 -0.06328426 -0.12897321 -0.11196526  0.21201206  0.18361791]
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Progress: 0.7% ... Training loss: 0.476 ... Validation loss: 0.770hidden_inputs = [-0.09936978 -0.36470651  0.2488693   0.50349682 -0.5012223  -0.53538131]
hidden_outputs = [ 0.47517798  0.40982073  0.56189818  0.62328075  0.37725347  0.36926266]
final_inputs = [-0.4699153]
final_outputs = [-0.4699153]
error = [-0.1004825]
output_error_term = [-0.1004825]
hidden_error = [ 0.0800595   0.04022657  0.08234503  0.07240093 -0.14686637 -0.11725991]
hidden_error_term = [ 0.01996555  0.00972951  0.02027076  0.01699987 -0.0345038  -0.02731074]
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Progress: 0.7% ... Training loss: 0.486 ... Validation loss: 0.752hidden_inputs = [ 0.44818796  0.42006533  0.27574035  0.28185529 -1.09116303 -0.82439344]
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final_outputs = [-0.81247171]
error = [ 0.01052556]
output_error_term = [ 0.01052556]
hidden_error = [-0.00830225 -0.00394802 -0.0084681  -0.00744016  0.01602216  0.01287292]
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Progress: 0.7% ... Training loss: 0.477 ... Validation loss: 0.746hidden_inputs = [-1.35403461 -0.91095304 -1.05166325 -1.02972552  0.81591806  0.7307896 ]
hidden_outputs = [ 0.20521155  0.28680485  0.25890584  0.26313732  0.69336917  0.67497852]
final_inputs = [ 1.17739718]
final_outputs = [ 1.17739718]
error = [-0.61210543]
output_error_term = [-0.61210543]
hidden_error = [ 0.50412257  0.25024012  0.51377087  0.45253813 -0.93084219 -0.74460701]
hidden_error_term = [ 0.08222227  0.05118607  0.09857907  0.08774537 -0.19790483 -0.16335376]
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Progress: 0.8% ... Training loss: 0.474 ... Validation loss: 0.744hidden_inputs = [-0.03847284 -0.23171258 -0.0573106  -0.01999755 -0.1818605  -0.15974028]
hidden_outputs = [ 0.49038298  0.44232965  0.48567627  0.49500078  0.45465977  0.46014963]
final_inputs = [-0.10147691]
final_outputs = [-0.10147691]
error = [-0.86586093]
output_error_term = [-0.86586093]
hidden_error = [ 0.71426706  0.35324628  0.72769787  0.64368519 -1.32701577 -1.0591346 ]
hidden_error_term = [ 0.1785007   0.08713672  0.18177517  0.16090521 -0.32902595 -0.26310169]
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delta_weights_h_o = [[ 4.47133576]
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self.weights_hidden_to_output = [[-0.80396184]
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Progress: 0.8% ... Training loss: 0.475 ... Validation loss: 0.742hidden_inputs = [ 0.24936155  0.45142972  0.27122286 -0.21388649  0.22667565 -0.25944562]
hidden_outputs = [ 0.56201935  0.61097911  0.56739309  0.4467313   0.55642751  0.43549999]
final_inputs = [-0.07250606]
final_outputs = [-0.07250606]
error = [-0.63020508]
output_error_term = [-0.63020508]
hidden_error = [ 0.50666084  0.2429498   0.52336588  0.45809244 -0.98169199 -0.78726695]
hidden_error_term = [ 0.12471639  0.05774519  0.12846443  0.11322325 -0.24229723 -0.19354151]
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delta_weights_h_o = [[-12.60972156]
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self.weights_hidden_to_output = [[-0.86306991]
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Progress: 0.8% ... Training loss: 0.483 ... Validation loss: 0.774hidden_inputs = [-0.71996853 -0.27113377 -0.91782314 -0.12422837  0.40038222  0.29235963]
hidden_outputs = [ 0.32739991  0.43262878  0.28540165  0.46898279  0.59877949  0.57257371]
final_inputs = [ 0.47588219]
final_outputs = [ 0.47588219]
error = [ 0.08940955]
output_error_term = [ 0.08940955]
hidden_error = [-0.0771667  -0.03981212 -0.07973378 -0.07015058  0.13360295  0.10600123]
hidden_error_term = [-0.01699282 -0.00977233 -0.01626151 -0.01747016  0.03209712  0.025942  ]
delta_weights_i_h = [[-2.02012565 -1.24510076 -2.24533394 -1.74125916  2.91098935  2.55415847]
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Progress: 0.8% ... Training loss: 0.458 ... Validation loss: 0.734hidden_inputs = [-0.41576966 -0.08149022  0.20997912 -0.90869081  0.9098812   0.62112009]
hidden_outputs = [ 0.39752948  0.47963871  0.55230275  0.28726781  0.71297585  0.65047325]
final_inputs = [ 0.70961223]
final_outputs = [ 0.70961223]
error = [-0.10021604]
output_error_term = [-0.10021604]
hidden_error = [ 0.08259876  0.03974691  0.08530053  0.07500012 -0.15533877 -0.12439892]
hidden_error_term = [ 0.01978238  0.00992025  0.02109179  0.0153559  -0.03178873 -0.02828306]
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Progress: 0.8% ... Training loss: 0.454 ... Validation loss: 0.729hidden_inputs = [ 0.03864701  0.06811411 -0.43101931 -0.1602548  -0.89124182 -0.55794251]
hidden_outputs = [ 0.50966055  0.51702195  0.39388296  0.46002182  0.29085363  0.36402366]
final_inputs = [-0.40491961]
final_outputs = [-0.40491961]
error = [-0.34740904]
output_error_term = [-0.34740904]
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Progress: 0.8% ... Training loss: 0.450 ... Validation loss: 0.724hidden_inputs = [-0.38279582  0.0197151  -0.36975295 -0.80923447  0.74237869  0.52735785]
hidden_outputs = [ 0.40545276  0.50492862  0.40860072  0.30805365  0.67751579  0.62886666]
final_inputs = [ 0.70051163]
final_outputs = [ 0.70051163]
error = [-0.09111544]
output_error_term = [-0.09111544]
hidden_error = [ 0.07658784  0.03832539  0.07944712  0.06881094 -0.14240633 -0.11355164]
hidden_error_term = [ 0.01846233  0.00958042  0.01919809  0.01466751 -0.03111409 -0.0265022 ]
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Progress: 0.8% ... Training loss: 0.450 ... Validation loss: 0.723hidden_inputs = [-0.17427086  0.1558044  -0.69168641 -0.71162542  0.30145121  0.36046561]
hidden_outputs = [ 0.45654222  0.5388725   0.33365803  0.32923978  0.57479724  0.58915314]
final_inputs = [ 0.45814159]
final_outputs = [ 0.45814159]
error = [-0.29530293]
output_error_term = [-0.29530293]
hidden_error = [ 0.25325324  0.12937472  0.263532    0.22667084 -0.46238377 -0.36902041]
hidden_error_term = [ 0.06283502  0.03214818  0.05859116  0.0500582  -0.11300908 -0.08932202]
delta_weights_i_h = [[ 1.39590659  0.61833601  1.12147076  1.06603239 -2.91563567 -2.10482018]
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Progress: 0.8% ... Training loss: 0.452 ... Validation loss: 0.733hidden_inputs = [ 0.25549726 -0.25196079  0.32398921 -0.90738383  0.01541714  0.46712884]
hidden_outputs = [ 0.5635291   0.43734094  0.58029614  0.28753549  0.50385421  0.61470397]
final_inputs = [ 0.12333353]
final_outputs = [ 0.12333353]
error = [-0.21409545]
output_error_term = [-0.21409545]
hidden_error = [ 0.18570358  0.096255    0.19233055  0.16520515 -0.33434114 -0.26647396]
hidden_error_term = [ 0.0456764   0.02368584  0.04684259  0.03384373 -0.08358032 -0.06311249]
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Progress: 0.8% ... Training loss: 0.441 ... Validation loss: 0.714hidden_inputs = [-0.31900334 -0.22908537  0.00540011 -0.4171297   0.53346997  1.07374382]
hidden_outputs = [ 0.42091866  0.44297782  0.50135002  0.39720379  0.63029206  0.74530823]
final_inputs = [ 0.6835052]
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error = [-0.60887544]
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Progress: 0.8% ... Training loss: 0.438 ... Validation loss: 0.717hidden_inputs = [ 0.65526573  0.50712412  0.26530689  0.27937904 -0.5794083  -0.08347727]
hidden_outputs = [ 0.6581961   0.62413206  0.56594039  0.56939398  0.35906876  0.47914279]
final_inputs = [-0.5727333]
final_outputs = [-0.5727333]
error = [ 0.34965803]
output_error_term = [ 0.34965803]
hidden_error = [-0.29553872 -0.15047341 -0.30819019 -0.26191347  0.55633999  0.44237717]
hidden_error_term = [-0.06648853 -0.03529974 -0.07570749 -0.06421712  0.12803519  0.11040185]
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Progress: 0.8% ... Training loss: 0.442 ... Validation loss: 0.710hidden_inputs = [-0.10604135  0.07792398 -0.39712358 -0.6795077   0.12362666 -0.06353693]
hidden_outputs = [ 0.47351448  0.51947114  0.40200363  0.33637119  0.53086736  0.48412111]
final_inputs = [ 0.30634568]
final_outputs = [ 0.30634568]
error = [-1.31778796]
output_error_term = [-1.31778796]
hidden_error = [ 1.09803309  0.53518792  1.13748008  0.96581539 -2.16060981 -1.72848121]
hidden_error_term = [ 0.27373802  0.13359408  0.27344647  0.21559473 -0.53809384 -0.43168449]
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Progress: 0.9% ... Training loss: 0.430 ... Validation loss: 0.699hidden_inputs = [-0.19854011  0.11070537 -0.0010791  -0.40371267 -0.39450307 -0.31969574]
hidden_outputs = [ 0.45052738  0.52764811  0.49973023  0.40042066  0.40263375  0.4207499 ]
final_inputs = [-0.17573856]
final_outputs = [-0.17573856]
error = [-0.16862395]
output_error_term = [-0.16862395]
hidden_error = [ 0.14638137  0.07341715  0.15115941  0.12883979 -0.27398773 -0.21833836]
hidden_error_term = [ 0.03623707  0.01829817  0.03778984  0.03093237 -0.06589948 -0.0532133 ]
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Progress: 0.9% ... Training loss: 0.428 ... Validation loss: 0.696hidden_inputs = [-0.04340009  0.17056838 -0.17376985 -0.46240883  0.46259768  0.4452692 ]
hidden_outputs = [ 0.48915168  0.54253901  0.45666652  0.38641454  0.61363024  0.60951386]
final_inputs = [ 0.42927792]
final_outputs = [ 0.42927792]
error = [-1.03275405]
output_error_term = [-1.03275405]
hidden_error = [ 0.89894247  0.45138181  0.92828449  0.78781244 -1.6893246  -1.34478968]
hidden_error_term = [ 0.22462983  0.11202865  0.230328    0.18678902 -0.40051888 -0.32006897]
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Progress: 0.9% ... Training loss: 0.441 ... Validation loss: 0.709hidden_inputs = [ 0.05759033  0.34502785  0.30983515 -0.1889514   0.09094189  0.18199974]
hidden_outputs = [ 0.5143936   0.58541133  0.57684502  0.45290219  0.52271982  0.54537476]
final_inputs = [-0.08544233]
final_outputs = [-0.08544233]
error = [ 1.38397053]
output_error_term = [ 1.38397053]
hidden_error = [-1.23868169 -0.64106715 -1.28185158 -1.08512054  2.22321276  1.76571073]
hidden_error_term = [-0.3094138  -0.15559014 -0.31289336 -0.26887312  0.55465559  0.43779232]
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Progress: 0.9% ... Training loss: 0.425 ... Validation loss: 0.693hidden_inputs = [-0.56522515  0.17472731 -0.53192428 -0.67435354  0.16084061  0.54343478]
hidden_outputs = [ 0.36233932  0.54357103  0.37006819  0.3375227   0.54012369  0.63261107]
final_inputs = [ 0.59219851]
final_outputs = [ 0.59219851]
error = [ 0.70632969]
output_error_term = [ 0.70632969]
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Progress: 0.9% ... Training loss: 0.453 ... Validation loss: 0.712hidden_inputs = [-0.41646688  0.32014915 -0.32237197 -0.54867395  0.24472533  0.96664282]
hidden_outputs = [ 0.3973625   0.5793606   0.42009779  0.36617212  0.5608778   0.72444984]
final_inputs = [ 0.76819983]
final_outputs = [ 0.76819983]
error = [-0.28009087]
output_error_term = [-0.28009087]
hidden_error = [ 0.23565145  0.11140941  0.24306318  0.20281319 -0.47965451 -0.3874641 ]
hidden_error_term = [ 0.0564304   0.02715068  0.05921399  0.04707093 -0.11813598 -0.07734646]
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Progress: 0.9% ... Training loss: 0.427 ... Validation loss: 0.689hidden_inputs = [-0.71273324 -0.61466859 -0.54941561  0.02764533  0.58356816  0.56702694]
hidden_outputs = [ 0.32899517  0.35099497  0.366       0.50691089  0.64188803  0.63807687]
final_inputs = [ 0.6867263]
final_outputs = [ 0.6867263]
error = [ 0.13767908]
output_error_term = [ 0.13767908]
hidden_error = [-0.12409288 -0.06422352 -0.12931591 -0.10918619  0.22655028  0.1805007 ]
hidden_error_term = [-0.02739442 -0.01462996 -0.03000698 -0.02729133  0.05207661  0.04168389]
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Progress: 0.9% ... Training loss: 0.419 ... Validation loss: 0.680hidden_inputs = [-0.69451462 -0.05698049 -0.56195069 -0.08627123  0.3396698   0.43397772]
hidden_outputs = [ 0.33302953  0.48575873  0.36309623  0.47844556  0.58411031  0.60682311]
final_inputs = [ 0.54179321]
final_outputs = [ 0.54179321]
error = [-0.27971955]
output_error_term = [-0.27971955]
hidden_error = [ 0.2497828   0.12862154  0.26225062  0.22042379 -0.46596803 -0.37197084]
hidden_error_term = [ 0.05548197  0.0321293   0.06064739  0.05500354 -0.1131955  -0.08874808]
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Progress: 0.9% ... Training loss: 0.416 ... Validation loss: 0.677hidden_inputs = [-0.46662407 -0.24966346  0.25693876 -0.2019873   0.16866715  0.24757292]
hidden_outputs = [ 0.38541559  0.43790634  0.56388362  0.44967416  0.5420671   0.56157902]
final_inputs = [ 0.33178164]
final_outputs = [ 0.33178164]
error = [-0.52177857]
output_error_term = [-0.52177857]
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Progress: 0.9% ... Training loss: 0.416 ... Validation loss: 0.671hidden_inputs = [-0.0735942   0.51904697  0.77672295  0.50043792 -1.18822584 -0.82219462]
hidden_outputs = [ 0.48160975  0.62692489  0.68497341  0.62256224  0.23357639  0.305298  ]
final_inputs = [-1.08762281]
final_outputs = [-1.08762281]
error = [ 0.10925886]
output_error_term = [ 0.10925886]
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Progress: 0.9% ... Training loss: 0.434 ... Validation loss: 0.700hidden_inputs = [-0.13342251  0.08176216  0.32642921 -0.0276798   0.0508389   0.44204737]
hidden_outputs = [ 0.46669377  0.52042916  0.58089029  0.49308049  0.51270699  0.60874677]
final_inputs = [ 0.28184495]
final_outputs = [ 0.28184495]
error = [-0.46632883]
output_error_term = [-0.46632883]
hidden_error = [ 0.39562032  0.18739907  0.41417876  0.3512762  -0.82123065 -0.66750756]
hidden_error_term = [ 0.09846622  0.04677156  0.10083462  0.08780223 -0.20517506 -0.15898304]
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Progress: 1.0% ... Training loss: 0.401 ... Validation loss: 0.659hidden_inputs = [-0.09262421 -0.11751519 -0.07049694 -0.40335983 -0.19259427 -0.07686122]
hidden_outputs = [ 0.47686049  0.47065497  0.48238306  0.40050537  0.45199971  0.48079415]
final_inputs = [ 0.01624698]
final_outputs = [ 0.01624698]
error = [-0.21175697]
output_error_term = [-0.21175697]
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Progress: 1.0% ... Training loss: 0.398 ... Validation loss: 0.646hidden_inputs = [-0.36895143 -0.73618244 -1.08096157 -0.2846019   0.16469377  0.04320666]
hidden_outputs = [ 0.40879442  0.3238395   0.25332409  0.42932592  0.54108063  0.51079998]
final_inputs = [ 0.5667651]
final_outputs = [ 0.5667651]
error = [ 0.21353583]
output_error_term = [ 0.21353583]
hidden_error = [-0.19312198 -0.09828319 -0.20336339 -0.17200498  0.37456337  0.30245476]
hidden_error_term = [-0.04667402 -0.02152082 -0.03846639 -0.04214211  0.09300872  0.07557841]
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delta_weights_h_o = [[ 1.93144083]
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self.weights_hidden_to_output = [[-0.89534718]
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Progress: 1.0% ... Training loss: 0.406 ... Validation loss: 0.651hidden_inputs = [-0.05560552 -0.37734542 -0.22792875  0.63342989 -0.10454139 -0.72791155]
hidden_outputs = [ 0.4861022   0.40676731  0.44326323  0.65326677  0.47388843  0.32565319]
final_inputs = [-0.22946464]
final_outputs = [-0.22946464]
error = [-0.63863819]
output_error_term = [-0.63863819]
hidden_error = [ 0.5718029   0.28081155  0.60122603  0.50638888 -1.14276197 -0.925529  ]
hidden_error_term = [ 0.14284028  0.06776198  0.14837112  0.11470179 -0.28491134 -0.20324912]
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delta_weights_h_o = [[-10.89234917]
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self.weights_hidden_to_output = [[-0.94640506]
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Progress: 1.0% ... Training loss: 0.409 ... Validation loss: 0.650hidden_inputs = [-0.88752011 -0.73258294 -1.01167639 -0.44435844  0.55348479  0.37103446]
hidden_outputs = [ 0.29162186  0.32462817  0.26665191  0.39070293  0.63494371  0.59170892]
final_inputs = [ 0.89666645]
final_outputs = [ 0.89666645]
error = [-0.38099221]
output_error_term = [-0.38099221]
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Progress: 1.0% ... Training loss: 0.398 ... Validation loss: 0.646hidden_inputs = [-0.50019829 -0.39019303  0.05280748 -0.26981413  0.19186778  0.1957174 ]
hidden_outputs = [ 0.37749407  0.40367083  0.5131988   0.43295273  0.54782033  0.54877376]
final_inputs = [ 0.33125649]
final_outputs = [ 0.33125649]
error = [-0.48266203]
output_error_term = [-0.48266203]
hidden_error = [ 0.4468882   0.22730507  0.4718713   0.39783449 -0.84175888 -0.68081551]
hidden_error_term = [ 0.10501528  0.05471703  0.11788562  0.09767022 -0.2085148  -0.1685843 ]
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delta_weights_h_o = [[ 3.32817035]
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self.weights_hidden_to_output = [[-0.91028144]
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Progress: 1.0% ... Training loss: 0.391 ... Validation loss: 0.641hidden_inputs = [-0.13797282  0.147713   -0.40471504 -0.93662714  0.8777501   1.31358318]
hidden_outputs = [ 0.46556141  0.53686125  0.40018003  0.28158215  0.70635577  0.78811213]
final_inputs = [ 1.08768285]
final_outputs = [ 1.08768285]
error = [ 0.91100346]
output_error_term = [ 0.91100346]
hidden_error = [-0.82926955 -0.41476354 -0.87959968 -0.73916796  1.60388824  1.30292149]
hidden_error_term = [-0.20633386 -0.10312732 -0.21113557 -0.14952898  0.33267416  0.21757668]
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Progress: 1.0% ... Training loss: 0.392 ... Validation loss: 0.636hidden_inputs = [-0.3269582  -0.5900104  -0.56808793 -0.5504515   0.1379994   0.06717194]
hidden_outputs = [ 0.41898092  0.35663247  0.36167814  0.36575966  0.5344452   0.51678667]
final_inputs = [ 0.47238203]
final_outputs = [ 0.47238203]
error = [ 0.3465103]
output_error_term = [ 0.3465103]
hidden_error = [-0.32060353 -0.1618714  -0.33926233 -0.28555672  0.61062696  0.49641924]
hidden_error_term = [-0.07804641 -0.03714071 -0.0783245  -0.06624331  0.15193225  0.12396492]
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delta_weights_h_o = [[-4.15013904]
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self.weights_hidden_to_output = [[-0.94468899]
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Progress: 1.0% ... Training loss: 0.403 ... Validation loss: 0.647hidden_inputs = [ 0.13136694  0.65004884  0.32606369 -0.09645564 -0.71639615 -0.06955723]
hidden_outputs = [ 0.53279459  0.65702147  0.58080131  0.47590477  0.32818707  0.4826177 ]
final_inputs = [-0.5417673]
final_outputs = [-0.5417673]
error = [ 0.61639706]
output_error_term = [ 0.61639706]
hidden_error = [-0.58230351 -0.30177443 -0.61612218 -0.51754757  1.08280274  0.87722174]
hidden_error_term = [-0.14494962 -0.06800314 -0.15000798 -0.12908641  0.23873669  0.21904039]
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Progress: 1.0% ... Training loss: 0.387 ... Validation loss: 0.624hidden_inputs = [-0.37922213 -0.21246084 -0.33431099 -0.31888141  0.7817801   0.22941527]
hidden_outputs = [ 0.40631452  0.44708369  0.41719206  0.42094838  0.68606364  0.55710358]
final_inputs = [ 0.77412464]
final_outputs = [ 0.77412464]
error = [-0.78219073]
output_error_term = [-0.78219073]
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Progress: 1.1% ... Training loss: 0.400 ... Validation loss: 0.638hidden_inputs = [-0.09537118 -0.53631394  0.14422424 -0.31800667 -0.22187793  0.80058842]
hidden_outputs = [ 0.47617526  0.36904547  0.53599369  0.42116161  0.44475696  0.69010034]
final_inputs = [ 0.2413302]
final_outputs = [ 0.2413302]
error = [-1.19764192]
output_error_term = [-1.19764192]
hidden_error = [ 1.15085741  0.59588132  1.2111956   1.01922873 -2.1255291  -1.72446466]
hidden_error_term = [ 0.2870611   0.13875151  0.30122974  0.24847217 -0.5248956  -0.36879722]
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Progress: 1.1% ... Training loss: 0.387 ... Validation loss: 0.619hidden_inputs = [-0.22869386  0.49571995 -0.4092541  -0.2323927  -0.11152835  0.01694153]
hidden_outputs = [ 0.44307442  0.62145298  0.39909099  0.44216189  0.47214678  0.50423528]
final_inputs = [ 0.18860865]
final_outputs = [ 0.18860865]
error = [-0.125005]
output_error_term = [-0.125005]
hidden_error = [ 0.11519434  0.05640548  0.12184317  0.10151121 -0.22982969 -0.18774489]
hidden_error_term = [ 0.0284253   0.01326934  0.02922011  0.02503822 -0.05727912 -0.04693285]
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Progress: 1.1% ... Training loss: 0.385 ... Validation loss: 0.608hidden_inputs = [-0.14685827 -0.60761848  0.06894583 -0.45373814 -0.57423242 -0.4916577 ]
hidden_outputs = [ 0.46335128  0.35260265  0.51722963  0.38847236  0.36026079  0.37950313]
final_inputs = [-0.18678778]
final_outputs = [-0.18678778]
error = [-0.80260228]
output_error_term = [-0.80260228]
hidden_error = [ 0.75186504  0.36949318  0.79269894  0.65879448 -1.48227151 -1.21388226]
hidden_error_term = [ 0.18695641  0.08434569  0.19793942  0.15650426 -0.34162349 -0.28584561]
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Progress: 1.1% ... Training loss: 0.379 ... Validation loss: 0.610hidden_inputs = [ 0.99802042  0.29939238  0.31982534  0.14819123 -0.96845526 -0.39286654]
hidden_outputs = [ 0.73066919  0.57429397  0.57928169  0.53698016  0.27518851  0.40302743]
final_inputs = [-0.88691057]
final_outputs = [-0.88691057]
error = [-0.03080976]
output_error_term = [-0.03080976]
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hidden_error_term = [ 0.00574659  0.00355641  0.00749784  0.00640714 -0.0112341  -0.01105897]
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Progress: 1.1% ... Training loss: 0.374 ... Validation loss: 0.615hidden_inputs = [ 0.44039991 -0.15794327  0.71440026  0.4531265  -0.52322091 -0.26965204]
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error = [ 0.3518483]
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Progress: 1.1% ... Training loss: 0.371 ... Validation loss: 0.612hidden_inputs = [-0.25451239 -0.01062568 -0.40792474 -0.3754427  -0.12146523 -0.23522542]
hidden_outputs = [ 0.43671316  0.4973436   0.39940983  0.40722653  0.46967097  0.4414633 ]
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error = [-0.06964354]
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Progress: 1.1% ... Training loss: 0.373 ... Validation loss: 0.611hidden_inputs = [ 0.11917185  0.36160613  0.1725391   0.23555515 -0.05425319 -0.0419326 ]
hidden_outputs = [ 0.52975775  0.58942918  0.54302808  0.558618    0.48644003  0.48951839]
final_inputs = [-0.09616596]
final_outputs = [-0.09616596]
error = [ 0.1487435]
output_error_term = [ 0.1487435]
hidden_error = [-0.13922954 -0.0686455  -0.14632239 -0.12160377  0.27894207  0.22800812]
hidden_error_term = [-0.03468409 -0.01661238 -0.03630969 -0.0299831   0.06968423  0.05697698]
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delta_weights_h_o = [[-1.59228526]
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self.weights_hidden_to_output = [[-0.94350167]
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Progress: 1.1% ... Training loss: 0.374 ... Validation loss: 0.599hidden_inputs = [ 0.07707334 -0.41301514 -0.40394403 -0.58161759  0.3281263  -0.57117875]
hidden_outputs = [ 0.5192588   0.39818937  0.40036511  0.35856047  0.58130341  0.36096488]
final_inputs = [ 0.29256695]
final_outputs = [ 0.29256695]
error = [-0.36127665]
output_error_term = [-0.36127665]
hidden_error = [ 0.34086512  0.16771306  0.35965003  0.29648562 -0.68371174 -0.56053034]
hidden_error_term = [ 0.08508985  0.04018985  0.08634222  0.06819017 -0.16640843 -0.1292971 ]
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Progress: 1.1% ... Training loss: 0.365 ... Validation loss: 0.584hidden_inputs = [-0.32292854 -0.63190515 -0.68247812 -0.74085034 -0.1004316   0.03812389]
hidden_outputs = [ 0.41996221  0.34707868  0.33570844  0.32281823  0.47491318  0.50952982]
final_inputs = [ 0.49339997]
final_outputs = [ 0.49339997]
error = [-0.76057968]
output_error_term = [-0.76057968]
hidden_error = [ 0.73808141  0.37135473  0.78089439  0.64257453 -1.44015258 -1.17709648]
hidden_error_term = [ 0.17979217  0.08415458  0.17414592  0.14047105 -0.35913179 -0.29416722]
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Progress: 1.1% ... Training loss: 0.364 ... Validation loss: 0.581hidden_inputs = [ 0.59061017 -0.12728079  0.08991483 -0.49035442 -1.004335   -0.65428227]
hidden_outputs = [ 0.64350514  0.46822269  0.52246358  0.37981008  0.26808996  0.34202519]
final_inputs = [-0.70084416]
final_outputs = [-0.70084416]
error = [-0.18379783]
output_error_term = [-0.18379783]
hidden_error = [ 0.18011311  0.09218019  0.1921986   0.15777029 -0.34870687 -0.28391368]
hidden_error_term = [ 0.04131908  0.02295196  0.04795266  0.03716348 -0.06842247 -0.06389306]
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   -2.84831894e-02  -1.93289545e-01]
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Progress: 1.1% ... Training loss: 0.358 ... Validation loss: 0.582hidden_inputs = [ 0.99488213  0.44962857  0.29192284  0.22809312 -1.11111452 -0.68630374]
hidden_outputs = [ 0.73005115  0.61055092  0.57246681  0.55677733  0.24766317  0.33485583]
final_inputs = [-1.07943999]
final_outputs = [-1.07943999]
error = [ 0.1562066]
output_error_term = [ 0.1562066]
hidden_error = [-0.15202819 -0.07632996 -0.16172177 -0.13327137  0.29877988  0.244171  ]
hidden_error_term = [-0.02996118 -0.01814962 -0.03958117 -0.03288822  0.0556705   0.05438357]
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delta_weights_h_o = [[-5.60555675]
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self.weights_hidden_to_output = [[-0.99952678]
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self.weights_input_to_hidden = [[ -2.42699992e-01  -2.82921114e-01  -3.64210849e-01  -4.73259338e-01
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   -1.87404478e-01  -1.53557974e-01]
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   -4.38615473e-02  -7.55129083e-02]
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   -3.20976284e-02  -1.96077305e-01]
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   -2.11908340e-01  -1.17358489e-01]
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Progress: 1.2% ... Training loss: 0.378 ... Validation loss: 0.603hidden_inputs = [ 0.14767988  0.18884024  0.56518226 -0.14162581  0.29561457 -0.14418093]
hidden_outputs = [ 0.53685302  0.54707026  0.63765076  0.46465261  0.57337011  0.46401708]
final_inputs = [-0.13403522]
final_outputs = [-0.13403522]
error = [ 1.12934533]
output_error_term = [ 1.12934533]
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Progress: 1.2% ... Training loss: 0.362 ... Validation loss: 0.593hidden_inputs = [-0.85522647 -0.01119063 -0.52463279 -0.91578177  0.37037881  0.49943643]
hidden_outputs = [ 0.29833764  0.49720237  0.37176957  0.28581817  0.59155051  0.62232688]
final_inputs = [ 0.98955952]
final_outputs = [ 0.98955952]
error = [-0.14861497]
output_error_term = [-0.14861497]
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Progress: 1.2% ... Training loss: 0.356 ... Validation loss: 0.583hidden_inputs = [ 0.12530834  0.29695056  0.46671793 -0.26460904 -0.95635403 -0.61900752]
hidden_outputs = [ 0.53128616  0.57369689  0.61460664  0.43423104  0.27760877  0.35000721]
final_inputs = [-0.75003513]
final_outputs = [-0.75003513]
error = [ 0.00873259]
output_error_term = [ 0.00873259]
hidden_error = [-0.00854269 -0.00437688 -0.0091465  -0.00761238  0.01673666  0.01365872]
hidden_error_term = [-0.00212731 -0.00107045 -0.00216649 -0.00187017  0.00335641  0.00310739]
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Progress: 1.2% ... Training loss: 0.362 ... Validation loss: 0.602hidden_inputs = [-0.20541674 -0.54629221  0.07514485 -0.34907779 -0.19351355 -0.47217485]
hidden_outputs = [ 0.44882563  0.36672507  0.51877738  0.41360607  0.45177202  0.38410161]
final_inputs = [ 0.00738062]
final_outputs = [ 0.00738062]
error = [-0.92510095]
output_error_term = [-0.92510095]
hidden_error = [ 0.88314901  0.4394408   0.94464963  0.78374597 -1.79828988 -1.47400992]
hidden_error_term = [ 0.21847445  0.10205476  0.23582933  0.19008668 -0.44538976 -0.34870294]
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Progress: 1.2% ... Training loss: 0.360 ... Validation loss: 0.588hidden_inputs = [ 0.28276018 -0.34848548  0.63339465  0.16527988 -1.23148904 -0.1315415 ]
hidden_outputs = [ 0.57022279  0.41374974  0.65325879  0.54122616  0.22592092  0.46716196]
final_inputs = [-0.79278628]
final_outputs = [-0.79278628]
error = [-0.05877738]
output_error_term = [-0.05877738]
hidden_error = [ 0.05862203  0.03032301  0.06258938  0.05221813 -0.11282349 -0.09212127]
hidden_error_term = [ 0.01436643  0.00735518  0.01417723  0.01296578 -0.01973065 -0.02293098]
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Progress: 1.2% ... Training loss: 0.355 ... Validation loss: 0.586hidden_inputs = [ 0.11092791  0.65357556  0.18928983 -0.02092503 -0.80918746 -0.09178904]
hidden_outputs = [ 0.52770357  0.65781575  0.54718166  0.49476893  0.30806367  0.47706884]
final_inputs = [-0.50919658]
final_outputs = [-0.50919658]
error = [-0.18800151]
output_error_term = [-0.18800151]
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Progress: 1.2% ... Training loss: 0.348 ... Validation loss: 0.573hidden_inputs = [ 0.29509975  0.13552824 -0.34705123  0.12325666 -0.72686608 -0.60717845]
hidden_outputs = [ 0.57324417  0.53383029  0.41409767  0.53077521  0.32588282  0.3527031 ]
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final_outputs = [-0.5187753]
error = [-0.02405722]
output_error_term = [-0.02405722]
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Progress: 1.2% ... Training loss: 0.346 ... Validation loss: 0.566hidden_inputs = [ 0.12147995  0.65856939  0.20043706 -0.01332416 -0.82992277 -0.10609146]
hidden_outputs = [ 0.53033269  0.65893895  0.54994217  0.49666901  0.3036614   0.47350198]
final_inputs = [-0.5340992]
final_outputs = [-0.5340992]
error = [-0.16309889]
output_error_term = [-0.16309889]
hidden_error = [ 0.16204973  0.08419271  0.17314139  0.14363242 -0.31925863 -0.26170142]
hidden_error_term = [ 0.04036333  0.01892134  0.04285349  0.03590651 -0.06750761 -0.0652416 ]
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self.weights_hidden_to_output = [[-0.99768062]
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Progress: 1.2% ... Training loss: 0.346 ... Validation loss: 0.561hidden_inputs = [ 0.39497319  0.64623787  1.20893603  0.41172765 -1.25601508 -1.11704991]
hidden_outputs = [ 0.59747932  0.65616217  0.77011064  0.60150206  0.22166064  0.24655891]
final_inputs = [-1.4442203]
final_outputs = [-1.4442203]
error = [ 0.41623884]
output_error_term = [ 0.41623884]
hidden_error = [-0.41527343 -0.21541    -0.43991904 -0.36771723  0.8221323   0.67349112]
hidden_error_term = [-0.09987234 -0.04859938 -0.07788337 -0.08814084  0.14184018  0.12511284]
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delta_weights_h_o = [[-3.98491357]
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Progress: 1.2% ... Training loss: 0.347 ... Validation loss: 0.564hidden_inputs = [-0.52376139  0.16914221 -0.00827672 -0.92817076  0.73725765  0.8612326 ]
hidden_outputs = [ 0.37197312  0.54218503  0.49793083  0.28329598  0.67639589  0.70291812]
final_inputs = [ 1.00949645]
final_outputs = [ 1.00949645]
error = [ 1.03329432]
output_error_term = [ 1.03329432]
hidden_error = [-1.05019891 -0.54849593 -1.10869065 -0.92783799  2.03587506  1.66304647]
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Progress: 1.3% ... Training loss: 0.349 ... Validation loss: 0.572hidden_inputs = [-0.5687874   0.29188533  0.06398547  0.12651796 -1.19793752 -0.62604419]
hidden_outputs = [ 0.36151667  0.57245763  0.51599091  0.53158737  0.23184232  0.34840805]
final_inputs = [-0.59818091]
final_outputs = [-0.59818091]
error = [-0.41877443]
output_error_term = [-0.41877443]
hidden_error = [ 0.41129538  0.20717602  0.43505974  0.36388301 -0.84065261 -0.68830326]
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Progress: 1.3% ... Training loss: 0.347 ... Validation loss: 0.562hidden_inputs = [-0.08581836 -0.58143868  0.0254077   0.19064497 -0.53954942 -0.71358855]
hidden_outputs = [ 0.47855857  0.35860162  0.50635158  0.54751741  0.3682924   0.32880639]
final_inputs = [-0.46298434]
final_outputs = [-0.46298434]
error = [ 0.04143905]
output_error_term = [ 0.04143905]
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hidden_error_term = [-0.01056574 -0.00509049 -0.01123962 -0.00932712  0.01916554  0.0148038 ]
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   -2.94484996e-02  -6.06611935e-02]
 [ -6.50081919e-02   6.97248676e-03  -1.90775026e-01   2.32843899e-02
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   -4.01099436e-02  -1.98936058e-01]
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   -2.07741034e-01  -1.13669500e-01]
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Progress: 1.3% ... Training loss: 0.361 ... Validation loss: 0.560hidden_inputs = [ 0.51154295  0.18598767  0.74174812 -0.49061273  0.10844307  0.15247536]
hidden_outputs = [ 0.62516811  0.54636335  0.677378    0.37974923  0.52708423  0.53804516]
final_inputs = [ 0.0643515]
final_outputs = [ 0.0643515]
error = [-0.11652203]
output_error_term = [-0.11652203]
hidden_error = [ 0.11436095  0.05728332  0.12180997  0.10124796 -0.23876267 -0.1958997 ]
hidden_error_term = [ 0.02679854  0.01419769  0.02661999  0.02384792 -0.05951552 -0.04869137]
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delta_weights_h_o = [[-5.09764354]
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self.weights_hidden_to_output = [[-1.00534866]
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self.weights_input_to_hidden = [[ -2.49341114e-01  -2.92243102e-01  -3.77939337e-01  -4.82143443e-01
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   -3.30940100e-02  -1.91715196e-01]
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Progress: 1.3% ... Training loss: 0.347 ... Validation loss: 0.541hidden_inputs = [-0.67679677 -0.5614152   0.06732607 -0.56203901  0.37167267  0.53626488]
hidden_outputs = [ 0.33697661  0.36322007  0.51682516  0.3630758   0.59186309  0.63094311]
final_inputs = [ 0.86126695]
final_outputs = [ 0.86126695]
error = [ 0.10647789]
output_error_term = [ 0.10647789]
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Progress: 1.3% ... Training loss: 0.349 ... Validation loss: 0.555hidden_inputs = [-0.07486859 -0.55752235  0.3477219   0.17264938 -0.13046608 -0.04928483]
hidden_outputs = [ 0.48129159  0.36412093  0.58606504  0.54305545  0.46742967  0.48768129]
final_inputs = [ 0.02600393]
final_outputs = [ 0.02600393]
error = [-0.41998394]
output_error_term = [-0.41998394]
hidden_error = [ 0.41809183  0.21023054  0.44505964  0.37053725 -0.86569534 -0.70968303]
hidden_error_term = [ 0.10437662  0.04867612  0.10796827  0.09194742 -0.21550548 -0.17731306]
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Progress: 1.3% ... Training loss: 0.336 ... Validation loss: 0.547hidden_inputs = [-0.32970018 -0.65083497  0.23473456 -0.13962667 -0.20450307 -0.27009083]
hidden_outputs = [ 0.41831358  0.3428014   0.55841566  0.46514993  0.44905167  0.4328848 ]
final_inputs = [-0.00858035]
final_outputs = [-0.00858035]
error = [-0.39642577]
output_error_term = [-0.39642577]
hidden_error = [ 0.40552201  0.20925025  0.43153772  0.36000452 -0.806371   -0.65674847]
hidden_error_term = [ 0.09867459  0.0471417   0.10641186  0.08956389 -0.19949963 -0.16122883]
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Progress: 1.3% ... Training loss: 0.336 ... Validation loss: 0.549hidden_inputs = [-0.23253974  0.04628347 -0.23234083 -0.60031997  0.102639    0.19329358]
hidden_outputs = [ 0.44212562  0.5115688   0.44217469  0.35427049  0.52563725  0.5481735 ]
final_inputs = [ 0.44712971]
final_outputs = [ 0.44712971]
error = [-0.70328331]
output_error_term = [-0.70328331]
hidden_error = [ 0.72143199  0.37248984  0.76959357  0.63942025 -1.43132234 -1.16467286]
hidden_error_term = [ 0.1779416   0.09307261  0.18982505  0.14627564 -0.35688982 -0.28846538]
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Progress: 1.3% ... Training loss: 0.344 ... Validation loss: 0.543hidden_inputs = [-0.65093898  0.23628967 -0.47480587 -0.03849897  0.01237702 -0.23329662]
hidden_outputs = [ 0.34277797  0.55879909  0.38347939  0.49037645  0.50309421  0.44193895]
final_inputs = [ 0.3330961]
final_outputs = [ 0.3330961]
error = [-0.126153]
output_error_term = [-0.126153]
hidden_error = [ 0.12651452  0.06333723  0.13441858  0.1119935  -0.26278618 -0.21505181]
hidden_error_term = [ 0.02850135  0.01561533  0.03177964  0.027988   -0.06569403 -0.05303799]
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Progress: 1.3% ... Training loss: 0.340 ... Validation loss: 0.535hidden_inputs = [ 0.48874401 -0.00280906  0.39709809 -0.20891816 -0.23569225  0.28794298]
hidden_outputs = [ 0.61981051  0.49929774  0.59799025  0.44795961  0.4413482   0.57149247]
final_inputs = [-0.03445619]
final_outputs = [-0.03445619]
error = [-0.19413214]
output_error_term = [-0.19413214]
hidden_error = [ 0.19710299  0.09904454  0.20885629  0.17385923 -0.4046779  -0.33089192]
hidden_error_term = [ 0.04644642  0.02476109  0.05020862  0.04299396 -0.09977737 -0.08103174]
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Progress: 1.4% ... Training loss: 0.339 ... Validation loss: 0.529hidden_inputs = [ 0.5752966   0.02752921  0.40978067 -0.03303972 -1.32682696 -0.8182621 ]
hidden_outputs = [ 0.63998444  0.50688187  0.60103529  0.49174082  0.20968471  0.30613269]
final_inputs = [-1.03890321]
final_outputs = [-1.03890321]
error = [ 0.24247011]
output_error_term = [ 0.24247011]
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hidden_error_term = [-0.05689946 -0.03124437 -0.06273501 -0.05424118  0.0841155   0.08814631]
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Progress: 1.4% ... Training loss: 0.330 ... Validation loss: 0.530hidden_inputs = [ 0.11755745 -0.05604855  0.0278784   0.62353116 -0.59598808 -0.34777758]
hidden_outputs = [ 0.52935556  0.48599153  0.50696915  0.65102123  0.35526209  0.41392145]
final_inputs = [-0.51931177]
final_outputs = [-0.51931177]
error = [-0.15032104]
output_error_term = [-0.15032104]
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hidden_error_term = [ 0.03874626  0.01994347  0.04128795  0.03123584 -0.07152411 -0.06175905]
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Progress: 1.4% ... Training loss: 0.346 ... Validation loss: 0.530hidden_inputs = [ 0.74805888  0.57962937  0.0978364  -0.32755999 -1.32186337 -1.21936676]
hidden_outputs = [ 0.67875559  0.64098212  0.52443961  0.41883443  0.21050844  0.22804791]
final_inputs = [-1.1024929]
final_outputs = [-1.1024929]
error = [ 0.12412895]
output_error_term = [ 0.12412895]
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Progress: 1.4% ... Training loss: 0.334 ... Validation loss: 0.529hidden_inputs = [ 0.47699269  0.47090993  0.28437008 -0.45037671 -0.37408924 -0.55588781]
hidden_outputs = [ 0.61703749  0.6155991   0.57061728  0.3892712   0.40755329  0.36449947]
final_inputs = [-0.51875186]
final_outputs = [-0.51875186]
error = [-0.4706382]
output_error_term = [-0.4706382]
hidden_error = [ 0.4942565   0.25712596  0.53001908  0.43654129 -0.98082259 -0.80041376]
hidden_error_term = [ 0.11679391  0.06084548  0.12986167  0.10378295 -0.23682315 -0.18540753]
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delta_weights_h_o = [[ 6.16022573]
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self.weights_hidden_to_output = [[-1.02130751]
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Progress: 1.4% ... Training loss: 0.330 ... Validation loss: 0.534hidden_inputs = [-0.39017018 -0.51436851 -0.24125298  0.06369373 -0.16929549 -0.552825  ]
hidden_outputs = [ 0.40367633  0.37417     0.4399776   0.51591805  0.45777693  0.36520924]
final_inputs = [ 0.03843201]
final_outputs = [ 0.03843201]
error = [-0.94512623]
output_error_term = [-0.94512623]
hidden_error = [ 0.96526452  0.49169647  1.03913116  0.85366699 -1.99164303 -1.63151414]
hidden_error_term = [ 0.23236017  0.115139    0.25603912  0.21320044 -0.49436008 -0.37823629]
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delta_weights_h_o = [[-3.68412403]
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self.weights_hidden_to_output = [[-1.03857684]
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Progress: 1.4% ... Training loss: 0.325 ... Validation loss: 0.523hidden_inputs = [-0.08619041 -0.48383305  0.11976933 -0.16000484 -0.60046682 -0.13238636]
hidden_outputs = [ 0.47846573  0.38134742  0.52990659  0.46008391  0.3542369   0.46695166]
final_inputs = [-0.15963637]
final_outputs = [-0.15963637]
error = [-0.82975369]
output_error_term = [-0.82975369]
hidden_error = [ 0.86176297  0.44123831  0.92458525  0.75893911 -1.74741231 -1.43109426]
hidden_error_term = [ 0.21504112  0.10409763  0.23031936  0.18852556 -0.39972602 -0.35621053]
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delta_weights_h_o = [[ 1.44864775]
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Progress: 1.4% ... Training loss: 0.325 ... Validation loss: 0.523hidden_inputs = [ 0.31388207 -0.31731543 -0.2305366  -0.02457684 -0.84387017 -0.77927569]
hidden_outputs = [ 0.57783255  0.42133014  0.44261976  0.4938561   0.30072031  0.31447601]
final_inputs = [-0.56974617]
final_outputs = [-0.56974617]
error = [-0.43067]
output_error_term = [-0.43067]
hidden_error = [ 0.44435941  0.2253402   0.47690574  0.39142762 -0.91426407 -0.74980093]
hidden_error_term = [ 0.10839796  0.05494043  0.11765623  0.09784213 -0.1922584  -0.16164272]
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Progress: 1.4% ... Training loss: 0.323 ... Validation loss: 0.515hidden_inputs = [-0.05944114 -0.16897824 -0.26155025 -0.61637811 -0.2722611  -0.23227558]
hidden_outputs = [ 0.48514409  0.45785567  0.43498266  0.35060564  0.43235208  0.44219078]
final_inputs = [ 0.1336247]
final_outputs = [ 0.1336247]
error = [-0.53863082]
output_error_term = [-0.53863082]
hidden_error = [ 0.56261078  0.28568101  0.60271201  0.49634155 -1.14808029 -0.93972303]
hidden_error_term = [ 0.14052853  0.07091284  0.14813019  0.1130077  -0.28176618 -0.23179029]
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delta_weights_h_o = [[-2.25369606]
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self.weights_hidden_to_output = [[-1.05508442]
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Progress: 1.4% ... Training loss: 0.326 ... Validation loss: 0.522hidden_inputs = [ 0.03975761 -0.71245143 -0.51684454 -0.28807795  0.06354847  0.32493625]
hidden_outputs = [ 0.50993809  0.32905739  0.37359038  0.42847448  0.51588177  0.58052678]
final_inputs = [ 0.5667918]
final_outputs = [ 0.5667918]
error = [-0.51972733]
output_error_term = [-0.51972733]
hidden_error = [ 0.54835621  0.28122025  0.5894583   0.48391101 -1.1054651  -0.90265032]
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Progress: 1.4% ... Training loss: 0.326 ... Validation loss: 0.515hidden_inputs = [-0.75504948 -0.19243219 -0.50907582 -0.56649598  0.0156992   0.04495968]
hidden_outputs = [ 0.31972204  0.45203986  0.3754102   0.36204575  0.50392472  0.51123803]
final_inputs = [ 0.60833765]
final_outputs = [ 0.60833765]
error = [ 0.98789558]
output_error_term = [ 0.98789558]
hidden_error = [-1.04875032 -0.54013513 -1.12282093 -0.92584339  2.10378676  1.71546553]
hidden_error_term = [-0.22810304 -0.13379138 -0.26327611 -0.21384078  0.52591429  0.42864973]
delta_weights_i_h = [[ 0.37483594  0.09047045  0.52254687  0.2964919  -1.02158912 -0.76743339]
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delta_weights_h_o = [[ 2.98132107]
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self.weights_hidden_to_output = [[-1.04762543]
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self.weights_input_to_hidden = [[-0.2199136  -0.28194095 -0.34769683 -0.45881423  0.23494228  0.06923791]
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Progress: 1.4% ... Training loss: 0.322 ... Validation loss: 0.509hidden_inputs = [-0.03598078 -0.28941052  0.26646245 -0.15844838 -0.87324843 -0.15635145]
hidden_outputs = [ 0.49100578  0.42814819  0.56622424  0.46047057  0.29457882  0.46099157]
final_inputs = [-0.3573329]
final_outputs = [-0.3573329]
error = [ 0.01297039]
output_error_term = [ 0.01297039]
hidden_error = [-0.01358811 -0.00685104 -0.01453444 -0.01197491  0.02786277  0.02279092]
hidden_error_term = [-0.00339593 -0.00167739 -0.00356987 -0.00297502  0.00578994  0.00566305]
delta_weights_i_h = [[-1.91200238 -1.01793066 -2.03477425 -1.66766812  3.96256515  3.32650238]
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Progress: 1.5% ... Training loss: 0.324 ... Validation loss: 0.516hidden_inputs = [ 0.00191657  0.24502421  0.37986094 -0.40256625 -0.75392609 -0.21108413]
hidden_outputs = [ 0.50047914  0.56095141  0.59383956  0.40069593  0.31996643  0.44742404]
final_inputs = [-0.34639837]
final_outputs = [-0.34639837]
error = [ 0.55885453]
output_error_term = [ 0.55885453]
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Progress: 1.5% ... Training loss: 0.329 ... Validation loss: 0.516hidden_inputs = [ 0.72265269  0.52609449  0.14189828  0.17533579 -1.26586336 -0.63768943]
hidden_outputs = [ 0.67319089  0.62857175  0.53541517  0.54372199  0.2199662   0.34576903]
final_inputs = [-1.00348696]
final_outputs = [-1.00348696]
error = [ 0.1905147]
output_error_term = [ 0.1905147]
hidden_error = [-0.19549264 -0.09775558 -0.20974248 -0.17421688  0.41465597  0.3403596 ]
hidden_error_term = [-0.04300934 -0.02282293 -0.05217255 -0.04322118  0.07114711  0.0769937 ]
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delta_weights_h_o = [[-5.2806951 ]
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self.weights_hidden_to_output = [[-1.05088219]
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Progress: 1.5% ... Training loss: 0.320 ... Validation loss: 0.504hidden_inputs = [ 0.01667366 -0.2670162  -0.13904625  0.01534302 -0.0571697   0.212668  ]
hidden_outputs = [ 0.50416832  0.43363976  0.46529434  0.50383568  0.48571147  0.55296752]
final_inputs = [ 0.27515083]
final_outputs = [ 0.27515083]
error = [ 0.70362012]
output_error_term = [ 0.70362012]
hidden_error = [-0.73942185 -0.37993455 -0.79340012 -0.6552237   1.52516058  1.24718199]
hidden_error_term = [-0.18484262 -0.09331053 -0.19739439 -0.16379628  0.38097877  0.30829646]
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Progress: 1.5% ... Training loss: 0.321 ... Validation loss: 0.504hidden_inputs = [ 0.43984575  0.45356674  0.74274648 -0.41595441 -0.79668322 -0.08128591]
hidden_outputs = [ 0.60822228  0.61148692  0.67759614  0.39748523  0.31073546  0.4796897 ]
final_inputs = [-0.55470342]
final_outputs = [-0.55470342]
error = [ 0.10559285]
output_error_term = [ 0.10559285]
hidden_error = [-0.10986151 -0.05621919 -0.11812086 -0.09771601  0.22960708  0.18794784]
hidden_error_term = [-0.02617867 -0.01335603 -0.02580464 -0.02340208  0.049177    0.04690943]
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Progress: 1.5% ... Training loss: 0.321 ... Validation loss: 0.509hidden_inputs = [-0.43478914 -0.57851282 -0.46484716 -0.41715485 -0.11733762  0.10551921]
hidden_outputs = [ 0.39298331  0.35927487  0.38583657  0.39719777  0.4706992   0.52635535]
final_inputs = [ 0.57412338]
final_outputs = [ 0.57412338]
error = [-0.04742303]
output_error_term = [-0.04742303]
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Progress: 1.5% ... Training loss: 0.336 ... Validation loss: 0.523hidden_inputs = [ 0.34081128  0.24504507  0.02200583 -0.40478681 -0.20433418  0.25209672]
hidden_outputs = [ 0.58438758  0.56095655  0.50550124  0.4001628   0.44909345  0.56269251]
final_inputs = [ 0.02542454]
final_outputs = [ 0.02542454]
error = [-0.13272563]
output_error_term = [-0.13272563]
hidden_error = [ 0.14264861  0.07540854  0.15374516  0.12796587 -0.28412068 -0.231683  ]
hidden_error_term = [ 0.03464631  0.01857194  0.03843164  0.03071597 -0.07029388 -0.05701015]
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Progress: 1.5% ... Training loss: 0.321 ... Validation loss: 0.503hidden_inputs = [ 0.59451818 -0.18241725  0.21594629 -0.25925347 -0.68845415 -0.6976867 ]
hidden_outputs = [ 0.64440115  0.45452173  0.55377775  0.43554723  0.33437704  0.33232532]
final_inputs = [-0.6197428]
final_outputs = [-0.6197428]
error = [ 0.17614529]
output_error_term = [ 0.17614529]
hidden_error = [-0.18363966 -0.09491541 -0.19766689 -0.16469175  0.38488629  0.31538787]
hidden_error_term = [-0.04208072 -0.02353254 -0.04884506 -0.04048878  0.08566377  0.0699799 ]
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Progress: 1.5% ... Training loss: 0.318 ... Validation loss: 0.502hidden_inputs = [-0.6271208  -0.43460647  0.14432625 -0.27213035  0.48216942  0.78309675]
hidden_outputs = [ 0.34816367  0.39302689  0.53601906  0.43238417  0.61826002  0.68634715]
final_inputs = [ 0.99632398]
final_outputs = [ 0.99632398]
error = [-1.40684315]
output_error_term = [-1.40684315]
hidden_error = [ 1.47324475  0.7621436   1.58690219  1.32631112 -3.08378708 -2.52299189]
hidden_error_term = [ 0.3343466   0.1818145   0.39466674  0.32551402 -0.72781867 -0.54313642]
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Progress: 1.5% ... Training loss: 0.339 ... Validation loss: 0.527hidden_inputs = [ 1.005095    0.71864982  0.47806125  0.69364056 -1.22869463 -1.10311179]
hidden_outputs = [ 0.73205914  0.67230963  0.61728996  0.6667763   0.22640998  0.24915729]
final_inputs = [-1.62321729]
final_outputs = [-1.62321729]
error = [ 0.74408835]
output_error_term = [ 0.74408835]
hidden_error = [-0.80283211 -0.4276587  -0.86580244 -0.72508173  1.59720485  1.29925126]
hidden_error_term = [-0.15747436 -0.09421723 -0.20453982 -0.16110277  0.27974803  0.24306124]
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Progress: 1.6% ... Training loss: 0.318 ... Validation loss: 0.500hidden_inputs = [-0.16974182 -0.40326255 -0.22813897  0.02828161  0.08293425  0.31287485]
hidden_outputs = [ 0.45766614  0.40052873  0.44321135  0.50706993  0.52072169  0.57758682]
final_inputs = [ 0.51805979]
final_outputs = [ 0.51805979]
error = [-0.33868196]
output_error_term = [-0.33868196]
hidden_error = [ 0.35306067  0.18244301  0.3820272   0.31620924 -0.74535673 -0.60882736]
hidden_error_term = [ 0.08763243  0.04380556  0.09427478  0.0790365  -0.18601913 -0.14854187]
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Progress: 1.6% ... Training loss: 0.322 ... Validation loss: 0.499hidden_inputs = [-0.29897821 -0.32871049 -0.35632492 -0.55288472  0.0268378   0.28592023]
hidden_outputs = [ 0.42580729  0.41855441  0.41184949  0.36519539  0.50670905  0.57099705]
final_inputs = [ 0.5948599]
final_outputs = [ 0.5948599]
error = [ 0.18544103]
output_error_term = [ 0.18544103]
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Progress: 1.6% ... Training loss: 0.316 ... Validation loss: 0.501hidden_inputs = [ 0.0112697  -0.04140059  0.11093689  0.26629438  0.14244304 -0.03585729]
hidden_outputs = [ 0.50281739  0.48965133  0.52770581  0.56618296  0.53555067  0.49103664]
final_inputs = [ 0.09245222]
final_outputs = [ 0.09245222]
error = [ 0.42873507]
output_error_term = [ 0.42873507]
hidden_error = [-0.45538932 -0.23918476 -0.49260946 -0.40966539  0.93888665  0.76330227]
hidden_error_term = [-0.11384372 -0.05977057 -0.12277423 -0.10062194  0.23353505  0.19076424]
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Progress: 1.6% ... Training loss: 0.314 ... Validation loss: 0.509hidden_inputs = [-0.15547471  0.0614036   0.27649305 -0.30671959 -0.29651766 -0.26184023]
hidden_outputs = [ 0.46120943  0.51534608  0.56868624  0.42391565  0.42640899  0.43491139]
final_inputs = [-0.10318216]
final_outputs = [-0.10318216]
error = [-0.42862425]
output_error_term = [-0.42862425]
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Progress: 1.6% ... Training loss: 0.314 ... Validation loss: 0.508hidden_inputs = [-1.00596804 -0.72770936 -0.89843626 -1.18862835  0.85026799  1.10589047]
hidden_outputs = [ 0.26776965  0.32569759  0.28937195  0.23350434  0.70062336  0.75136217]
final_inputs = [ 1.87229335]
final_outputs = [ 1.87229335]
error = [-0.03899871]
output_error_term = [-0.03899871]
hidden_error = [ 0.04119617  0.02138429  0.04471907  0.03717521 -0.08577689 -0.06992188]
hidden_error_term = [ 0.00807729  0.00469639  0.00919584  0.00665362 -0.01799173 -0.0130626 ]
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Progress: 1.6% ... Training loss: 0.312 ... Validation loss: 0.503hidden_inputs = [-0.42465913 -0.03843979 -0.02483642 -0.66040866  0.56616285  0.80830257]
hidden_outputs = [ 0.3954024   0.49039123  0.49379121  0.34064782  0.6378773   0.69174767]
final_inputs = [ 1.09096537]
final_outputs = [ 1.09096537]
error = [ 1.51415711]
output_error_term = [ 1.51415711]
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hidden_error_term = [-0.38025963 -0.20639444 -0.43369775 -0.32179071  0.77458748  0.58309726]
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Progress: 1.6% ... Training loss: 0.327 ... Validation loss: 0.525hidden_inputs = [ 0.79222414  0.31162997  0.13571133 -0.15837051 -0.99423417 -0.39437267]
hidden_outputs = [ 0.6883087   0.57728307  0.53387586  0.46048992  0.27007656  0.40266511]
final_inputs = [-0.6975682]
final_outputs = [-0.6975682]
error = [-0.21463908]
output_error_term = [-0.21463908]
hidden_error = [ 0.2212155   0.11318825  0.24132053  0.19937585 -0.48134806 -0.39369132]
hidden_error_term = [ 0.04745954  0.02762103  0.0600532   0.04953273 -0.09489065 -0.09469297]
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delta_weights_h_o = [[-9.35999366]
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self.weights_hidden_to_output = [[-1.0745144 ]
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Progress: 1.6% ... Training loss: 0.318 ... Validation loss: 0.504hidden_inputs = [-0.09160152  0.03837235  0.45213206 -0.34987588  0.39922789  0.59468192]
hidden_outputs = [ 0.47711562  0.50959191  0.61114603  0.41341252  0.59850214  0.64443867]
final_inputs = [ 0.55708934]
final_outputs = [ 0.55708934]
error = [-0.27296346]
output_error_term = [-0.27296346]
hidden_error = [ 0.29330317  0.15521552  0.3185469   0.2650232  -0.60158829 -0.48925033]
hidden_error_term = [ 0.07317219  0.0387896   0.07570157  0.06426882 -0.14456006 -0.11210558]
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Progress: 1.6% ... Training loss: 0.317 ... Validation loss: 0.505hidden_inputs = [-0.29853687 -0.15766835 -0.53291182 -0.63268036  0.26094168  0.6913817 ]
hidden_outputs = [ 0.4259152   0.46066437  0.36983801  0.34690302  0.56486776  0.66627422]
final_inputs = [ 0.96296497]
final_outputs = [ 0.96296497]
error = [-0.59614324]
output_error_term = [-0.59614324]
hidden_error = [ 0.63919912  0.33679771  0.6963655   0.57847639 -1.31704356 -1.07421622]
hidden_error_term = [ 0.1562915   0.0836783   0.16229345  0.13106037 -0.323719   -0.23885507]
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Progress: 1.6% ... Training loss: 0.350 ... Validation loss: 0.517hidden_inputs = [-0.43831679 -0.76343209 -1.10684383 -0.4295793   0.425715    0.26571967]
hidden_outputs = [ 0.39214212  0.31790159  0.24845976  0.3942268   0.60484999  0.56604179]
final_inputs = [ 1.2172103]
final_outputs = [ 1.2172103]
error = [-0.76217968]
output_error_term = [-0.76217968]
hidden_error = [ 0.78283947  0.39463025  0.85491104  0.69944599 -1.72832538 -1.41852535]
hidden_error_term = [ 0.18660284  0.08557169  0.15963541  0.16703612 -0.41308097 -0.34844441]
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Progress: 1.6% ... Training loss: 0.361 ... Validation loss: 0.529hidden_inputs = [ 0.36696111  0.05842195  0.13231712 -0.17522079 -0.85358211 -0.55904018]
hidden_outputs = [ 0.59072447  0.51460133  0.5330311   0.45630654  0.29868197  0.36376957]
final_inputs = [-0.76556946]
final_outputs = [-0.76556946]
error = [ 0.01324081]
output_error_term = [ 0.01324081]
hidden_error = [-0.01468059 -0.00792846 -0.01595469 -0.01320375  0.02886299  0.02343207]
hidden_error_term = [-0.00354931 -0.00198042 -0.00397127 -0.00327573  0.00604596  0.00542315]
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Progress: 1.7% ... Training loss: 0.311 ... Validation loss: 0.495hidden_inputs = [-0.41788293  0.56169806 -0.47106185 -0.5487993   0.09655611  0.42064788]
hidden_outputs = [ 0.39702346  0.63684535  0.38436495  0.36614303  0.52412029  0.60363827]
final_inputs = [ 0.69833293]
final_outputs = [ 0.69833293]
error = [-0.44728538]
output_error_term = [-0.44728538]
hidden_error = [ 0.47218025  0.24533548  0.51639946  0.4217941  -0.99228304 -0.80993648]
hidden_error_term = [ 0.11303798  0.05673956  0.12219485  0.09789095 -0.24749346 -0.19378468]
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Progress: 1.7% ... Training loss: 0.312 ... Validation loss: 0.487hidden_inputs = [ 0.05431687  0.32972953  0.39035298  0.45764953 -0.18323093 -0.55920616]
hidden_outputs = [ 0.51357588  0.58169356  0.59636767  0.61245643  0.45432     0.36373116]
final_inputs = [-0.4641402]
final_outputs = [-0.4641402]
error = [-0.08971843]
output_error_term = [-0.08971843]
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hidden_error_term = [ 0.02375417  0.01204194  0.02499991  0.02018274 -0.0494916  -0.03772984]
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Progress: 1.7% ... Training loss: 0.312 ... Validation loss: 0.486hidden_inputs = [ 0.28091813  0.23809305  0.81017335 -0.02399022 -0.89040379 -0.56102996]
hidden_outputs = [ 0.5697713   0.55924366  0.69214644  0.49400273  0.29102651  0.36330918]
final_inputs = [-0.86592189]
final_outputs = [-0.86592189]
error = [-0.05179844]
output_error_term = [-0.05179844]
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hidden_error_term = [ 0.01345246  0.00700188  0.01276519  0.01227918 -0.02385612 -0.02189224]
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Progress: 1.7% ... Training loss: 0.316 ... Validation loss: 0.494hidden_inputs = [ 0.07986956  0.3429252  -0.25739589 -0.46924797 -0.27163847  0.2591885 ]
hidden_outputs = [ 0.51995678  0.58490091  0.43600396  0.38479425  0.4325049   0.5644368 ]
final_inputs = [ 0.21251139]
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error = [-0.48520416]
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Progress: 1.7% ... Training loss: 0.311 ... Validation loss: 0.500hidden_inputs = [-0.42401652 -0.62414831 -0.19711565 -0.23542639  0.28836398  0.24759628]
hidden_outputs = [ 0.39555603  0.34883857  0.45088003  0.44141375  0.57159556  0.56158477]
final_inputs = [ 0.74518486]
final_outputs = [ 0.74518486]
error = [-0.26258896]
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Progress: 1.7% ... Training loss: 0.309 ... Validation loss: 0.502hidden_inputs = [ 0.45352484  0.23753564  0.18445884 -0.0482462  -0.56092659 -0.26807428]
hidden_outputs = [ 0.61147697  0.55910626  0.5459844   0.48794079  0.36333309  0.43337992]
final_inputs = [-0.42015938]
final_outputs = [-0.42015938]
error = [-0.0399773]
output_error_term = [-0.0399773]
hidden_error = [ 0.04182763  0.02161968  0.04581068  0.03766498 -0.08928621 -0.07341608]
hidden_error_term = [ 0.00993711  0.00532939  0.0113558   0.00941077 -0.02065388 -0.01802818]
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delta_weights_h_o = [[ 0.74043474]
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self.weights_hidden_to_output = [[-1.04281365]
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Progress: 1.7% ... Training loss: 0.309 ... Validation loss: 0.504hidden_inputs = [-0.38823292 -0.3709428  -0.57074192  0.03369659  0.46199486 -0.02468581]
hidden_outputs = [ 0.40414276  0.40831323  0.36106565  0.50842335  0.61348731  0.49382886]
final_inputs = [ 0.76735489]
final_outputs = [ 0.76735489]
error = [-0.45566372]
output_error_term = [-0.45566372]
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Progress: 1.7% ... Training loss: 0.307 ... Validation loss: 0.495hidden_inputs = [-0.29250489 -0.56400193 -0.63676017 -0.4254528   0.41192823  0.3484514 ]
hidden_outputs = [ 0.42739074  0.362622    0.34597927  0.39521268  0.60155014  0.586242  ]
final_inputs = [ 1.01293146]
final_outputs = [ 1.01293146]
error = [ 0.25803146]
output_error_term = [ 0.25803146]
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self.weights_hidden_to_output = [[-1.049556  ]
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Progress: 1.7% ... Training loss: 0.309 ... Validation loss: 0.505hidden_inputs = [ 0.15597527 -0.15012049  0.25392337 -0.56877379 -0.34561354 -0.32733308]
hidden_outputs = [ 0.53891495  0.4625402   0.56314194  0.36151982  0.41444653  0.41888967]
final_inputs = [-0.07945163]
final_outputs = [-0.07945163]
error = [-0.00028419]
output_error_term = [-0.00028419]
hidden_error = [ 0.00029827  0.00015326  0.00032551  0.00026783 -0.00064432 -0.00053032]
hidden_error_term = [  7.41155560e-05   3.80989097e-05   8.00789125e-05   6.18218545e-05
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Progress: 1.8% ... Training loss: 0.320 ... Validation loss: 0.503hidden_inputs = [ 0.17905078 -0.26328735  0.49020247  0.42158713 -0.51480625 -0.50589644]
hidden_outputs = [ 0.54464349  0.43455578  0.62015413  0.60386297  0.37406751  0.37615599]
final_inputs = [-0.50740086]
final_outputs = [-0.50740086]
error = [-0.01337944]
output_error_term = [-0.01337944]
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hidden_error_term = [ 0.0034784   0.00176336  0.0035981   0.00298483 -0.00718384 -0.00592589]
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Progress: 1.8% ... Training loss: 0.307 ... Validation loss: 0.483hidden_inputs = [ 0.71805405 -0.28722249  0.1708766  -0.44211856 -0.39579921 -0.45638495]
hidden_outputs = [ 0.67217836  0.42868398  0.54261551  0.39123628  0.40232204  0.38784376]
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final_outputs = [-0.32530293]
error = [-0.47664322]
output_error_term = [-0.47664322]
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Progress: 1.8% ... Training loss: 0.320 ... Validation loss: 0.489hidden_inputs = [ 0.56437009  0.49507426  0.15123587  0.04743003 -0.83075584 -0.36487896]
hidden_outputs = [ 0.63746309  0.62130107  0.53773707  0.51185528  0.30348527  0.40977902]
final_inputs = [-0.63385841]
final_outputs = [-0.63385841]
error = [ 0.0524345]
output_error_term = [ 0.0524345]
hidden_error = [-0.05535417 -0.02838829 -0.06022574 -0.04951097  0.12097097  0.09932922]
hidden_error_term = [-0.01279256 -0.00667937 -0.01497067 -0.01237078  0.02557108  0.02402378]
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delta_weights_h_o = [[-8.1572699 ]
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self.weights_hidden_to_output = [[-1.09391955]
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Progress: 1.8% ... Training loss: 0.318 ... Validation loss: 0.481hidden_inputs = [ 0.7908617   0.94021299  0.87274786  0.17595188 -1.87354563 -0.74652805]
hidden_outputs = [ 0.68801632  0.71914268  0.70531715  0.54387483  0.133132    0.32157829]
final_inputs = [-1.64532555]
final_outputs = [-1.64532555]
error = [ 0.65042244]
output_error_term = [ 0.65042244]
hidden_error = [-0.71150982 -0.37610627 -0.77444463 -0.63942685  1.47500819  1.20491417]
hidden_error_term = [-0.15272548 -0.07596462 -0.16096434 -0.15862581  0.17022755  0.26287094]
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Progress: 1.8% ... Training loss: 0.312 ... Validation loss: 0.480hidden_inputs = [ 0.63314665  0.3545977   0.81587328  0.30179992 -0.89784218 -0.43598165]
hidden_outputs = [ 0.65320261  0.58773206  0.69335965  0.57488246  0.28949413  0.39269888]
final_inputs = [-0.98484217]
final_outputs = [-0.98484217]
error = [ 0.02853044]
output_error_term = [ 0.02853044]
hidden_error = [-0.03053809 -0.01581865 -0.03329266 -0.02737226  0.06535675  0.05359303]
hidden_error_term = [-0.00691776 -0.00383291 -0.00707842 -0.00668958  0.01344305  0.01278121]
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delta_weights_h_o = [[ 2.29411492]
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self.weights_hidden_to_output = [[-1.05961502]
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Progress: 1.8% ... Training loss: 0.310 ... Validation loss: 0.495hidden_inputs = [ 0.10027397  0.24070879  0.42741266 -0.51772869 -0.57944351 -0.4020366 ]
hidden_outputs = [ 0.52504751  0.55988831  0.60525567  0.37338349  0.35906065  0.40082312]
final_inputs = [-0.32734198]
final_outputs = [-0.32734198]
error = [-0.49665639]
output_error_term = [-0.49665639]
hidden_error = [ 0.52626457  0.26877786  0.57412701  0.47204977 -1.14571937 -0.93954029]
hidden_error_term = [ 0.13123598  0.06623046  0.13717114  0.11044466 -0.26367139 -0.2256437 ]
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delta_weights_h_o = [[-7.88162016]
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self.weights_hidden_to_output = [[-1.09656011]
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Progress: 1.8% ... Training loss: 0.325 ... Validation loss: 0.488hidden_inputs = [-0.53408466 -0.47176971 -0.62671578 -0.81392622  0.48853871  0.2669198 ]
hidden_outputs = [ 0.36956471  0.38419746  0.3482556   0.30705447  0.61976213  0.56633656]
final_inputs = [ 1.11559817]
final_outputs = [ 1.11559817]
error = [ 0.51371339]
output_error_term = [ 0.51371339]
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 [ 0.19220033  0.13837417  0.27190008 -0.026677   -0.1088772   0.135952  ]
 [ 0.04535446 -0.13157744  0.11403801  0.09336911 -0.15003853  0.03455265]]
Progress: 1.8% ... Training loss: 0.307 ... Validation loss: 0.486hidden_inputs = [-0.64078456 -0.37706832 -0.17544779 -0.73025717  0.2961594   0.14715916]
hidden_outputs = [ 0.34506921  0.40683418  0.45625022  0.3251383   0.57350338  0.53672354]
final_inputs = [ 0.90108045]
final_outputs = [ 0.90108045]
error = [ 1.07004058]
output_error_term = [ 1.07004058]
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Progress: 1.8% ... Training loss: 0.316 ... Validation loss: 0.482hidden_inputs = [-0.19733302 -0.34600268 -0.29627988 -0.43095275  0.09852564  0.65695276]
hidden_outputs = [ 0.45082621  0.4143521   0.42646715  0.39389885  0.5246115   0.65857554]
final_inputs = [ 0.80955011]
final_outputs = [ 0.80955011]
error = [-0.78453786]
output_error_term = [-0.78453786]
hidden_error = [ 0.85254046  0.44331199  0.92909901  0.76676766 -1.78533039 -1.46499792]
hidden_error_term = [ 0.21107362  0.10757605  0.22725104  0.18306006 -0.44525118 -0.32941035]
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Progress: 1.8% ... Training loss: 0.305 ... Validation loss: 0.483hidden_inputs = [ 0.01951866 -0.01580938  0.16887563  0.68144373 -0.8591345  -0.77231144]
hidden_outputs = [ 0.50487951  0.49604774  0.54211886  0.66406085  0.2975202   0.31597931]
final_inputs = [-0.77619079]
final_outputs = [-0.77619079]
error = [-0.20768621]
output_error_term = [-0.20768621]
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hidden_error_term = [ 0.05517682  0.02808352  0.05985804  0.04398687 -0.10031775 -0.08538208]
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Progress: 1.9% ... Training loss: 0.304 ... Validation loss: 0.475hidden_inputs = [-0.42290268 -0.68150946 -0.54421328 -0.176272    0.27272447 -0.07540066]
hidden_outputs = [ 0.39582237  0.33592449  0.36720801  0.45604575  0.56776164  0.48115876]
final_inputs = [ 0.7212982]
final_outputs = [ 0.7212982]
error = [ 1.06237893]
output_error_term = [ 1.06237893]
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Progress: 1.9% ... Training loss: 0.318 ... Validation loss: 0.497hidden_inputs = [ 0.37931406  0.71543683  0.76019338  0.39873915 -1.38927504 -0.86319074]
hidden_outputs = [ 0.59370765  0.67160138  0.68139572  0.59838469  0.19952352  0.29667314]
final_inputs = [-1.28768663]
final_outputs = [-1.28768663]
error = [ 0.24867906]
output_error_term = [ 0.24867906]
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Progress: 1.9% ... Training loss: 0.303 ... Validation loss: 0.468hidden_inputs = [-0.68601747 -0.76372725 -0.94390048 -0.78003034  1.16623755  1.30595891]
hidden_outputs = [ 0.33491959  0.31783759  0.28011314  0.31431335  0.76246426  0.78683615]
final_inputs = [ 2.10403819]
final_outputs = [ 2.10403819]
error = [ 1.21226853]
output_error_term = [ 1.21226853]
hidden_error = [-1.31519519 -0.67354523 -1.43269548 -1.16502187  2.81862011  2.31766619]
hidden_error_term = [-0.2929577  -0.14603596 -0.28890271 -0.25108606  0.51048737  0.38873061]
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delta_weights_h_o = [[ 3.47955245]
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self.weights_hidden_to_output = [[-1.06859378]
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Progress: 1.9% ... Training loss: 0.305 ... Validation loss: 0.480hidden_inputs = [-0.04008915  0.19370407  0.09828728 -0.27442    -0.62433688  0.03847155]
hidden_outputs = [ 0.48997905  0.54827517  0.52455206  0.43182232  0.34879574  0.5096167 ]
final_inputs = [-0.04830627]
final_outputs = [-0.04830627]
error = [ 0.33243215]
output_error_term = [ 0.33243215]
hidden_error = [-0.35523493 -0.17933324 -0.38805846 -0.31551988  0.77515143  0.63922346]
hidden_error_term = [-0.08877306 -0.04441537 -0.09678069 -0.07741337  0.17606578  0.15974675]
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delta_weights_h_o = [[-5.92231434]
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self.weights_hidden_to_output = [[-1.09635463]
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Progress: 1.9% ... Training loss: 0.311 ... Validation loss: 0.475hidden_inputs = [ 0.15293677  0.14325328  0.46058729 -0.62276376 -0.84501621 -0.56710277]
hidden_outputs = [ 0.53815984  0.5357522   0.61315349  0.34915314  0.30047937  0.36190561]
final_inputs = [-0.5844228]
final_outputs = [-0.5844228]
error = [-0.40496726]
output_error_term = [-0.40496726]
hidden_error = [ 0.44398773  0.22934419  0.48336047  0.39355782 -0.93539187 -0.76775839]
hidden_error_term = [ 0.11035041  0.0570429   0.11465131  0.08943413 -0.19661144 -0.1772984 ]
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Progress: 1.9% ... Training loss: 0.309 ... Validation loss: 0.477hidden_inputs = [-0.73930535 -0.77387299 -1.44796052 -0.34224498  1.30160851  0.98488765]
hidden_outputs = [ 0.32315606  0.3156419   0.19031564  0.41526425  0.78610557  0.72807696]
final_inputs = [ 2.14738116]
final_outputs = [ 2.14738116]
error = [ 1.53830031]
output_error_term = [ 1.53830031]
hidden_error = [-1.62551144 -0.81437152 -1.78271788 -1.43701041  3.62176014  2.98676269]
hidden_error_term = [-0.35554198 -0.17591409 -0.27470898 -0.34893466  0.6089758   0.59132197]
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delta_weights_h_o = [[-4.91488707]
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Progress: 1.9% ... Training loss: 0.300 ... Validation loss: 0.466hidden_inputs = [-0.0176716  -0.23009877  0.14386977 -0.49732565 -0.4394352   0.10231516]
hidden_outputs = [ 0.49558222  0.44272778  0.53590553  0.37816936  0.39187556  0.5255565 ]
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delta_weights_h_o = [[-2.1531027 ]
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self.weights_hidden_to_output = [[-1.08982438]
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self.weights_input_to_hidden = [[-0.21125039 -0.29121989 -0.34467151 -0.46170513  0.23839001  0.07694102]
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Progress: 1.9% ... Training loss: 0.305 ... Validation loss: 0.469hidden_inputs = [-0.26307021 -0.29360188 -0.23950859  0.10588227 -0.13887365 -0.31423178]
hidden_outputs = [ 0.43460913  0.4271223   0.44040745  0.52644587  0.46533728  0.42208215]
final_inputs = [ 0.14814702]
final_outputs = [ 0.14814702]
error = [ 0.80305865]
output_error_term = [ 0.80305865]
hidden_error = [-0.87519289 -0.4525127  -0.95657609 -0.77433373  1.87448361  1.5382711 ]
hidden_error_term = [-0.21505593 -0.11072481 -0.23574696 -0.19304188  0.4663687   0.37522864]
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Progress: 1.9% ... Training loss: 0.303 ... Validation loss: 0.469hidden_inputs = [ 0.2502755  -0.05123425  0.37706845  0.9953096  -0.56535485 -0.78186313]
hidden_outputs = [ 0.56224431  0.48719424  0.59316585  0.73013539  0.36230936  0.31391848]
final_inputs = [-0.78089167]
final_outputs = [-0.78089167]
error = [-0.07618504]
output_error_term = [-0.07618504]
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Progress: 1.9% ... Training loss: 0.300 ... Validation loss: 0.468hidden_inputs = [ 0.05373198 -0.32523676  0.30954197  0.57320122 -0.84265971 -0.73977082]
hidden_outputs = [ 0.51342976  0.41940004  0.57677346  0.63950151  0.30097491  0.32305426]
final_inputs = [-0.73183823]
final_outputs = [-0.73183823]
error = [-0.28511711]
output_error_term = [-0.28511711]
hidden_error = [ 0.30628757  0.15637304  0.33487881  0.27064311 -0.67170109 -0.55173739]
hidden_error_term = [ 0.07651665  0.0380774   0.08174587  0.06239388 -0.14131853 -0.12065956]
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Progress: 1.9% ... Training loss: 0.309 ... Validation loss: 0.471hidden_inputs = [-0.08766724 -0.64516762  0.11127753  0.08100632 -0.34122718 -0.85224001]
hidden_outputs = [ 0.47809722  0.34407933  0.52779071  0.52024051  0.41551141  0.29896318]
final_inputs = [-0.31624652]
final_outputs = [-0.31624652]
error = [-0.45813435]
output_error_term = [-0.45813435]
hidden_error = [ 0.50230348  0.26297101  0.54911417  0.44490327 -1.07173921 -0.87537063]
hidden_error_term = [ 0.1253349   0.0593496   0.13685445  0.11104355 -0.26028438 -0.18346385]
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Progress: 2.0% ... Training loss: 0.304 ... Validation loss: 0.472hidden_inputs = [-0.03932765  0.11564865  0.52584291 -0.48768437 -0.13831688  0.01933898]
hidden_outputs = [ 0.49016935  0.52887998  0.62851302  0.38043922  0.4654758   0.50483459]
final_inputs = [ 0.18000454]
final_outputs = [ 0.18000454]
error = [-0.28730563]
output_error_term = [-0.28730563]
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Progress: 2.0% ... Training loss: 0.308 ... Validation loss: 0.477hidden_inputs = [ 0.08067829  0.13772769  0.28456665 -0.39290888 -0.07952977 -0.42678607]
hidden_outputs = [ 0.52015864  0.5343776   0.57066544  0.40301724  0.48012803  0.39489405]
final_inputs = [ 0.04292018]
final_outputs = [ 0.04292018]
error = [-0.71255299]
output_error_term = [-0.71255299]
hidden_error = [ 0.74985028  0.37621089  0.82476512  0.67037607 -1.69336431 -1.39143414]
hidden_error_term = [ 0.18715785  0.09360811  0.20207273  0.16128869 -0.42267238 -0.332487  ]
delta_weights_i_h = [[ 0.08857335 -0.09174757  0.03171926 -0.06071414  0.36915533  0.38301598]
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delta_weights_h_o = [[-2.6500229 ]
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self.weights_hidden_to_output = [[-1.06476517]
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self.weights_input_to_hidden = [[-0.22193846 -0.29821026 -0.35865052 -0.47124332  0.26817608  0.10232611]
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Progress: 2.0% ... Training loss: 0.303 ... Validation loss: 0.478hidden_inputs = [-0.12340971 -0.50922285 -0.28368464  0.21550708 -0.44379135 -0.13929182]
hidden_outputs = [ 0.46918667  0.37537572  0.42955067  0.55366922  0.39083794  0.46523324]
final_inputs = [ 0.11070592]
final_outputs = [ 0.11070592]
error = [-0.03607616]
output_error_term = [-0.03607616]
hidden_error = [ 0.03841264  0.01923889  0.04222034  0.0341934  -0.08575274 -0.07048194]
hidden_error_term = [ 0.00956669  0.00451092  0.01034554  0.00844986 -0.02041632 -0.01753529]
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Progress: 2.0% ... Training loss: 0.306 ... Validation loss: 0.464hidden_inputs = [-0.59034093 -0.88585387 -0.66802846 -0.73792237  0.77893597  0.38186866]
hidden_outputs = [ 0.35655663  0.29196618  0.33893844  0.32345863  0.68545075  0.59432372]
final_inputs = [ 1.55341002]
final_outputs = [ 1.55341002]
error = [ 0.20821488]
output_error_term = [ 0.20821488]
hidden_error = [-0.22324937 -0.11183237 -0.24512485 -0.19848209  0.49647658  0.4083097 ]
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Progress: 2.0% ... Training loss: 0.307 ... Validation loss: 0.465hidden_inputs = [-0.42885198  0.3012409   0.05113867  0.03814021 -1.59793714 -0.74024392]
hidden_outputs = [ 0.3944005   0.57474584  0.51278188  0.5095339   0.16827012  0.32295081]
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error = [-0.11625531]
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Progress: 2.0% ... Training loss: 0.308 ... Validation loss: 0.473hidden_inputs = [ 0.3500883  -0.2715945   0.06160997 -0.05297979 -0.81152562 -0.19047888]
hidden_outputs = [ 0.58663899  0.43251569  0.51539762  0.48675815  0.30756549  0.45252374]
final_inputs = [-0.35655193]
final_outputs = [-0.35655193]
error = [-0.26897643]
output_error_term = [-0.26897643]
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Progress: 2.0% ... Training loss: 0.309 ... Validation loss: 0.494hidden_inputs = [ 0.03307524  0.3265214   0.76925556 -0.35386311 -1.26555017 -0.12467418]
hidden_outputs = [ 0.50826806  0.58091274  0.68335983  0.41244594  0.22001994  0.46887177]
final_inputs = [-0.54469865]
final_outputs = [-0.54469865]
error = [-0.46123057]
output_error_term = [-0.46123057]
hidden_error = [ 0.4801012   0.23433693  0.52916058  0.42715291 -1.09863087 -0.90639198]
hidden_error_term = [ 0.11999248  0.05705006  0.11449933  0.1035138  -0.18853732 -0.22571973]
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delta_weights_h_o = [[-1.52671537]
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self.weights_hidden_to_output = [[-1.04807012]
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Progress: 2.0% ... Training loss: 0.313 ... Validation loss: 0.490hidden_inputs = [-0.26640689 -0.67025522 -0.08979053 -0.70700671 -0.87945429 -0.14475259]
hidden_outputs = [ 0.43378941  0.3384397   0.47756744  0.33026058  0.29329088  0.46387491]
final_inputs = [ 0.13870776]
final_outputs = [ 0.13870776]
error = [ 0.3879926]
output_error_term = [ 0.3879926]
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Progress: 2.0% ... Training loss: 0.304 ... Validation loss: 0.464hidden_inputs = [ 0.29638285  0.21265166  0.17393191  0.41725731 -1.31936902 -0.31699887]
hidden_outputs = [ 0.57355804  0.55296348  0.54337369  0.60282676  0.21092329  0.42140732]
final_inputs = [-0.83953243]
final_outputs = [-0.83953243]
error = [-0.00651817]
output_error_term = [-0.00651817]
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delta_weights_h_o = [[ 3.39979686]
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self.weights_hidden_to_output = [[-1.07373504]
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Progress: 2.0% ... Training loss: 0.300 ... Validation loss: 0.471hidden_inputs = [ 0.35444103 -0.00303379  0.16666719  0.27508955 -1.22636079 -0.72179769]
hidden_outputs = [ 0.5876941   0.49924155  0.54157061  0.56834195  0.22681901  0.32699724]
final_inputs = [-0.89611433]
final_outputs = [-0.89611433]
error = [ 0.17135096]
output_error_term = [ 0.17135096]
hidden_error = [-0.18398553 -0.09190816 -0.20035655 -0.16240503  0.40648051  0.33355889]
hidden_error_term = [-0.04458149 -0.02297699 -0.0497429  -0.03984273  0.07128536  0.07340632]
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Progress: 2.1% ... Training loss: 0.299 ... Validation loss: 0.468hidden_inputs = [ 0.56640422  0.20051033  0.61408145 -0.38747032 -1.32270845 -1.10014863]
hidden_outputs = [ 0.63793306  0.54996031  0.64887127  0.40432642  0.21036803  0.24971205]
final_inputs = [-1.15598966]
final_outputs = [-1.15598966]
error = [ 0.16108655]
output_error_term = [ 0.16108655]
hidden_error = [-0.17409409 -0.08765562 -0.18947063 -0.15342201  0.38062381  0.31218614]
hidden_error_term = [-0.04021129 -0.02169511 -0.04316849 -0.03695117  0.06322669  0.05848993]
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Progress: 2.1% ... Training loss: 0.297 ... Validation loss: 0.470hidden_inputs = [ 0.35240067  0.21040008 -0.52072843  0.23154058 -0.05687503  0.02193228]
hidden_outputs = [ 0.58719961  0.55240683  0.37268192  0.55762792  0.48578507  0.50548285]
final_inputs = [ 0.24237271]
final_outputs = [ 0.24237271]
error = [-0.34967381]
output_error_term = [-0.34967381]
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Progress: 2.1% ... Training loss: 0.298 ... Validation loss: 0.472hidden_inputs = [-0.51372992 -0.19385337 -0.49238542 -0.26096669 -0.93207659 -0.10572388]
hidden_outputs = [ 0.37431955  0.45168786  0.37933178  0.43512609  0.28250361  0.47359362]
final_inputs = [ 0.10513855]
final_outputs = [ 0.10513855]
error = [-0.19038742]
output_error_term = [-0.19038742]
hidden_error = [ 0.20263546  0.10059393  0.22091973  0.17863106 -0.45109225 -0.37035603]
hidden_error_term = [ 0.04745812  0.02491369  0.05201316  0.04390598 -0.09143429 -0.09233076]
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Progress: 2.1% ... Training loss: 0.299 ... Validation loss: 0.475hidden_inputs = [ -2.53781116e-01   3.32899126e-05  -3.39630611e-01  -6.81671637e-01
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final_inputs = [-0.05526692]
final_outputs = [-0.05526692]
error = [-0.10716473]
output_error_term = [-0.10716473]
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Progress: 2.1% ... Training loss: 0.298 ... Validation loss: 0.474hidden_inputs = [ 0.39974872  0.28899344  0.53243696  0.21307554 -0.6139956  -0.19463213]
hidden_outputs = [ 0.59862728  0.57174969  0.63005131  0.55306826  0.35114829  0.45149499]
final_inputs = [-0.48412249]
final_outputs = [-0.48412249]
error = [ 0.15629915]
output_error_term = [ 0.15629915]
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Progress: 2.1% ... Training loss: 0.307 ... Validation loss: 0.484hidden_inputs = [-0.32349445 -0.89152143 -0.83586486 -0.72745674  0.27332587  0.62412456]
hidden_outputs = [ 0.41982436  0.29079596  0.30240641  0.32575308  0.56790922  0.65115603]
final_inputs = [ 1.32368288]
final_outputs = [ 1.32368288]
error = [-1.42547092]
output_error_term = [-1.42547092]
hidden_error = [ 1.52977157  0.76675669  1.67123342  1.35613994 -3.35615744 -2.75393636]
hidden_error_term = [ 0.37260932  0.15813105  0.35255801  0.29785988 -0.8235619  -0.62556175]
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Progress: 2.1% ... Training loss: 0.301 ... Validation loss: 0.467hidden_inputs = [ 0.04950643 -0.74613549 -0.02814243  0.48866164 -0.27630624 -0.83731842]
hidden_outputs = [ 0.51237408  0.32166394  0.49296486  0.6197911   0.43135958  0.30209986]
final_inputs = [-0.24448884]
final_outputs = [-0.24448884]
error = [-0.48027453]
output_error_term = [-0.48027453]
hidden_error = [ 0.50922925  0.25315162  0.55570968  0.44898754 -1.14413114 -0.93881459]
hidden_error_term = [ 0.12722934  0.05523674  0.13889992  0.10580396 -0.2806422  -0.19793547]
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delta_weights_h_o = [[-3.13747391]
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self.weights_hidden_to_output = [[-1.07499475]
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self.weights_input_to_hidden = [[-0.19810776 -0.28822628 -0.33741225 -0.45587346  0.23523887  0.07480135]
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Progress: 2.1% ... Training loss: 0.298 ... Validation loss: 0.462hidden_inputs = [-0.36186541 -0.40793017 -0.15549628 -1.05758611  0.2216089   0.30445202]
hidden_outputs = [ 0.41050808  0.39940853  0.46120407  0.25777102  0.5551766   0.57553049]
final_inputs = [ 0.98950059]
final_outputs = [ 0.98950059]
error = [ 0.12709676]
output_error_term = [ 0.12709676]
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Progress: 2.1% ... Training loss: 0.309 ... Validation loss: 0.477hidden_inputs = [ 0.02627229  0.08492812 -0.13024655 -0.50150111 -0.3722295   0.03338586]
hidden_outputs = [ 0.5065677   0.52121928  0.46748432  0.37718797  0.4080024   0.50834569]
final_inputs = [ 0.17799577]
final_outputs = [ 0.17799577]
error = [-0.70980218]
output_error_term = [-0.70980218]
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Progress: 2.1% ... Training loss: 0.299 ... Validation loss: 0.471hidden_inputs = [-0.34486794 -0.25266739 -0.21071486 -0.30379037 -0.1761792   0.45870642]
hidden_outputs = [ 0.41462748  0.43716707  0.44751534  0.42463116  0.45606877  0.61270726]
final_inputs = [ 0.63973819]
final_outputs = [ 0.63973819]
error = [ 0.53198972]
output_error_term = [ 0.53198972]
hidden_error = [-0.57658702 -0.29372537 -0.62756341 -0.50547126  1.25847185  1.02715188]
hidden_error_term = [-0.13994432 -0.07227172 -0.15516214 -0.12349651  0.31218917  0.24374013]
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Progress: 2.2% ... Training loss: 0.303 ... Validation loss: 0.480hidden_inputs = [ 0.06380495 -0.1174627   0.67919472 -0.0400864  -1.78653893 -0.54102612]
hidden_outputs = [ 0.51594583  0.47066804  0.66355894  0.48997974  0.14349759  0.36794891]
final_inputs = [-1.01217712]
final_outputs = [-1.01217712]
error = [-0.01580433]
output_error_term = [-0.01580433]
hidden_error = [ 0.01707796  0.00865543  0.01863559  0.01501437 -0.03738951 -0.03056293]
hidden_error_term = [ 0.00426515  0.00215641  0.00416037  0.00375209 -0.0045954  -0.00710779]
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Progress: 2.2% ... Training loss: 0.300 ... Validation loss: 0.478hidden_inputs = [-0.30854694 -0.84746689 -0.23566535 -0.15962313  0.40065049  0.17670299]
hidden_outputs = [ 0.42346945  0.2999645   0.44135483  0.46017873  0.59884394  0.54406116]
final_inputs = [ 0.90935766]
final_outputs = [ 0.90935766]
error = [-0.23380479]
output_error_term = [-0.23380479]
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hidden_error_term = [ 0.06162737  0.02676468  0.06768674  0.05482697 -0.13357444 -0.1128415 ]
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Progress: 2.2% ... Training loss: 0.304 ... Validation loss: 0.482hidden_inputs = [-0.48690622  0.54538361 -0.043935   -0.47015346 -0.52387524  0.41147178]
hidden_outputs = [ 0.38062265  0.63306389  0.48901802  0.38457992  0.37194652  0.60144073]
final_inputs = [ 0.35675797]
final_outputs = [ 0.35675797]
error = [-0.48059823]
output_error_term = [-0.48059823]
hidden_error = [ 0.52014622  0.26247289  0.56546375  0.45442216 -1.1439541  -0.93341309]
hidden_error_term = [ 0.12262398  0.06097088  0.14129774  0.10755182 -0.26723032 -0.22374824]
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Progress: 2.2% ... Training loss: 0.300 ... Validation loss: 0.479hidden_inputs = [-0.39420193  0.38888086  0.09159316 -0.78830679 -0.5004657  -0.07743794]
hidden_outputs = [ 0.40270618  0.59601326  0.5228823   0.31253235  0.37743123  0.48065018]
final_inputs = [ 0.19679987]
final_outputs = [ 0.19679987]
error = [-0.12217011]
output_error_term = [-0.12217011]
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Progress: 2.2% ... Training loss: 0.299 ... Validation loss: 0.476hidden_inputs = [ 0.45325917 -0.21955473  0.11495377 -0.58677635 -0.63035539 -0.0757236 ]
hidden_outputs = [ 0.61141385  0.44533075  0.52870684  0.35737485  0.34742996  0.48107814]
final_inputs = [-0.10562882]
final_outputs = [-0.10562882]
error = [ 0.25744136]
output_error_term = [ 0.25744136]
hidden_error = [-0.2770959  -0.13982962 -0.30279248 -0.24412456  0.61049552  0.49830881]
hidden_error_term = [-0.06583437 -0.03453949 -0.07544859 -0.05606517  0.138413    0.12439879]
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Progress: 2.2% ... Training loss: 0.308 ... Validation loss: 0.486hidden_inputs = [-0.19660783  0.22657276  0.38429737 -0.62107534  0.72666456  0.36558552]
hidden_outputs = [ 0.45100576  0.55640211  0.59490916  0.34953692  0.67407291  0.59039186]
final_inputs = [ 1.04248022]
final_outputs = [ 1.04248022]
error = [-0.03063094]
output_error_term = [-0.03063094]
hidden_error = [ 0.03184961  0.01553623  0.03482871  0.02801986 -0.0737329  -0.06055883]
hidden_error_term = [ 0.00788595  0.00383463  0.00839345  0.00637062 -0.01619902 -0.0146449 ]
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delta_weights_h_o = [[-6.54429944]
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self.weights_hidden_to_output = [[-1.07046218]
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Progress: 2.2% ... Training loss: 0.297 ... Validation loss: 0.464hidden_inputs = [-0.43539123 -0.32077964 -0.0238949   0.14064476  0.68267221  0.22562378]
hidden_outputs = [ 0.39283969  0.42048575  0.49402656  0.53510334  0.66433485  0.55616787]
final_inputs = [ 0.95732633]
final_outputs = [ 0.95732633]
error = [ 0.50659355]
output_error_term = [ 0.50659355]
hidden_error = [-0.54228924 -0.2702975  -0.58964835 -0.47403908  1.21279661  0.99056984]
hidden_error_term = [-0.12934502 -0.06586542 -0.14739105 -0.11792564  0.27044644  0.24451738]
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delta_weights_h_o = [[-1.94848841]
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self.weights_hidden_to_output = [[-1.07959572]
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Progress: 2.2% ... Training loss: 0.293 ... Validation loss: 0.465hidden_inputs = [-0.72177191 -0.30307755 -0.71996065 -0.2484041   0.73382928  0.80512777]
hidden_outputs = [ 0.32700292  0.42480532  0.32740165  0.43821634  0.67564502  0.69107029]
final_inputs = [ 1.57733461]
final_outputs = [ 1.57733461]
error = [-0.45522421]
output_error_term = [-0.45522421]
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 [-0.13338988  0.12594788 -0.19836902 -0.10417989  0.13720525  0.01631983]
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 [ 0.09884114 -0.15269197  0.14387738 -0.00746815 -0.07824603 -0.1839883 ]
 [-0.25162675 -0.04713272 -0.00275037  0.1680573  -0.23000494 -0.11372891]
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Progress: 2.2% ... Training loss: 0.295 ... Validation loss: 0.474hidden_inputs = [ 0.03252253  0.17513247  0.30590292 -0.32757358 -0.26461809  0.07161471]
hidden_outputs = [ 0.50812992  0.54367155  0.5758849   0.41883113  0.43422882  0.51789603]
final_inputs = [ 0.13773384]
final_outputs = [ 0.13773384]
error = [ 0.59294959]
output_error_term = [ 0.59294959]
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hidden_error_term = [-0.15921937 -0.07959582 -0.16900913 -0.13588254  0.34784177  0.2879584 ]
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Progress: 2.2% ... Training loss: 0.294 ... Validation loss: 0.476hidden_inputs = [ 0.2092731  -0.27440867  0.04402899 -0.39053843 -0.69868133 -0.20506113]
hidden_outputs = [ 0.55212817  0.43182509  0.51100547  0.40358769  0.33210466  0.44891361]
final_inputs = [-0.10277069]
final_outputs = [-0.10277069]
error = [ 0.52472298]
output_error_term = [ 0.52472298]
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Progress: 2.3% ... Training loss: 0.294 ... Validation loss: 0.461hidden_inputs = [ 0.73820876  0.6264319   0.32413978 -0.39009772 -1.14464804 -0.34854412]
hidden_outputs = [ 0.67660404  0.65167997  0.58033282  0.40369378  0.241468    0.41373551]
final_inputs = [-0.72042464]
final_outputs = [-0.72042464]
error = [ 0.07284406]
output_error_term = [ 0.07284406]
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Progress: 2.3% ... Training loss: 0.309 ... Validation loss: 0.474hidden_inputs = [ 0.6375596   0.20880263 -0.200358   -0.91537342 -0.68717791 -0.06418657]
hidden_outputs = [ 0.6542016   0.55201183  0.45007739  0.28590153  0.33466116  0.48395886]
final_inputs = [-0.1092137]
final_outputs = [-0.1092137]
error = [ 0.19486957]
output_error_term = [ 0.19486957]
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hidden_error_term = [-0.04818407 -0.02720373 -0.05766278 -0.03855405  0.10339462  0.09403708]
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Progress: 2.3% ... Training loss: 0.296 ... Validation loss: 0.474hidden_inputs = [ 0.67296718  0.40099355  0.3918149  -0.74899772 -1.74878063 -0.93857417]
hidden_outputs = [ 0.66216724  0.59892635  0.59671952  0.32103973  0.14820106  0.28118844]
final_inputs = [-1.13801409]
final_outputs = [-1.13801409]
error = [ 0.09900652]
output_error_term = [ 0.09900652]
hidden_error = [-0.10586179 -0.05413831 -0.11609766 -0.09429103  0.23727893  0.19288192]
hidden_error_term = [-0.02368147 -0.01300476 -0.02793836 -0.02055292  0.0299535   0.03898558]
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Progress: 2.3% ... Training loss: 0.292 ... Validation loss: 0.467hidden_inputs = [-0.37066407  0.2817837   0.32861954 -0.29834183 -0.24571584 -0.22366258]
hidden_outputs = [ 0.40838057  0.56998347  0.58142345  0.42596289  0.43887826  0.44431629]
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Progress: 2.3% ... Training loss: 0.296 ... Validation loss: 0.473hidden_inputs = [ 0.28426542  0.45113206  0.07242584 -1.24289754 -0.7045811   0.43474638]
hidden_outputs = [ 0.57059164  0.61090836  0.51809855  0.22393203  0.33079732  0.60700649]
final_inputs = [ 0.27482397]
final_outputs = [ 0.27482397]
error = [ 0.24636333]
output_error_term = [ 0.24636333]
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self.weights_hidden_to_output = [[-1.06237128]
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Progress: 2.3% ... Training loss: 0.296 ... Validation loss: 0.473hidden_inputs = [-0.06251558 -0.71389507  0.38361998 -0.33472546 -1.10885874 -0.6128364 ]
hidden_outputs = [ 0.48437619  0.32873874  0.5947459   0.41709129  0.24808372  0.35141245]
final_inputs = [-0.50823243]
final_outputs = [-0.50823243]
error = [-0.47564457]
output_error_term = [-0.47564457]
hidden_error = [ 0.50531114  0.2602101   0.55706659  0.45381864 -1.14099947 -0.92796177]
hidden_error_term = [ 0.12620444  0.05742045  0.13426598  0.11033518 -0.21283997 -0.21150266]
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delta_weights_h_o = [[ 4.12902683]
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self.weights_hidden_to_output = [[-1.04301647]
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Progress: 2.3% ... Training loss: 0.297 ... Validation loss: 0.465hidden_inputs = [ 0.27221242  0.53980624  0.06410711 -0.54250825 -1.78163453 -0.43004096]
hidden_outputs = [ 0.56763597  0.63176734  0.51602129  0.36760429  0.14410142  0.39411655]
final_inputs = [-0.74780179]
final_outputs = [-0.74780179]
error = [-0.15337938]
output_error_term = [-0.15337938]
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Progress: 2.3% ... Training loss: 0.296 ... Validation loss: 0.477hidden_inputs = [-0.2669918  -0.24793006 -0.11854764 -0.10061384  0.37592382  0.26402863]
hidden_outputs = [ 0.43364575  0.43833305  0.47039775  0.47486774  0.5928896   0.56562636]
final_inputs = [ 0.81844426]
final_outputs = [ 0.81844426]
error = [-0.41303115]
output_error_term = [-0.41303115]
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Progress: 2.3% ... Training loss: 0.293 ... Validation loss: 0.479hidden_inputs = [-0.30689257  0.13151384 -0.00130779  0.5887225  -0.87774943 -0.34483053]
hidden_outputs = [ 0.42387341  0.53283115  0.49967305  0.64307197  0.29364437  0.41463656]
final_inputs = [-0.39861111]
final_outputs = [-0.39861111]
error = [ 0.04873555]
output_error_term = [ 0.04873555]
hidden_error = [-0.05103389 -0.0261681  -0.05628457 -0.04617069  0.11739308  0.09524413]
hidden_error_term = [-0.01246272 -0.00651382 -0.01407114 -0.01059758  0.02434936  0.023117  ]
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delta_weights_h_o = [[ 2.8742929 ]
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   -9.15732514e-02  -1.87931166e-01]
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Progress: 2.4% ... Training loss: 0.300 ... Validation loss: 0.492hidden_inputs = [ 0.47557078 -0.45947668 -0.09984996  0.125202   -0.68607105 -0.57230687]
hidden_outputs = [ 0.61670143  0.38710998  0.47505823  0.53125968  0.33490766  0.3607047 ]
final_inputs = [-0.34883715]
final_outputs = [-0.34883715]
error = [-0.26015204]
output_error_term = [-0.26015204]
hidden_error = [ 0.26891554  0.13506382  0.29647289  0.2432881  -0.63214868 -0.51497545]
hidden_error_term = [ 0.06356646  0.03204468  0.07393379  0.06058429 -0.14080765 -0.1187517 ]
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delta_weights_h_o = [[-6.04396993]
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self.weights_hidden_to_output = [[-1.06201718]
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   -2.03198039e-01  -1.17709265e-01]
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   -9.20479086e-02  -1.88362554e-01]
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Progress: 2.4% ... Training loss: 0.298 ... Validation loss: 0.481hidden_inputs = [-0.22384609 -0.4426255   0.18979967 -0.70677579  0.79348878  0.4746474 ]
hidden_outputs = [ 0.44427098  0.39111554  0.54730799  0.33031166  0.68857995  0.61648314]
final_inputs = [ 1.21798713]
final_outputs = [ 1.21798713]
error = [ 0.09156718]
output_error_term = [ 0.09156718]
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Progress: 2.4% ... Training loss: 0.307 ... Validation loss: 0.502hidden_inputs = [ 0.15722081 -0.36114283  0.40682771  0.14004683 -0.32560043 -0.43199872]
hidden_outputs = [ 0.53922444  0.41068295  0.60032698  0.5349546   0.41931149  0.39364916]
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final_outputs = [-0.13627893]
error = [-0.73733696]
output_error_term = [-0.73733696]
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Progress: 2.4% ... Training loss: 0.315 ... Validation loss: 0.482hidden_inputs = [-0.33348237  0.0659275   0.70092427 -0.24714479 -0.45705155 -0.24411382]
hidden_outputs = [ 0.41739355  0.51647591  0.66839266  0.43852639  0.38768551  0.43927282]
final_inputs = [-0.1908006]
final_outputs = [-0.1908006]
error = [-0.00470939]
output_error_term = [-0.00470939]
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hidden_error_term = [ 0.00124587  0.0006692   0.00125098  0.00113976 -0.0026931  -0.00225865]
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Progress: 2.4% ... Training loss: 0.291 ... Validation loss: 0.465hidden_inputs = [ 0.16738169  0.3578637   0.52073168  0.58432204 -0.30864489 -0.67574875]
hidden_outputs = [ 0.541748    0.5885232   0.62731884  0.6420613   0.42344554  0.3372108 ]
final_inputs = [-0.51489626]
final_outputs = [-0.51489626]
error = [-0.03896238]
output_error_term = [-0.03896238]
hidden_error = [ 0.04094361  0.02084289  0.04512525  0.03696579 -0.09528724 -0.07733837]
hidden_error_term = [ 0.01016454  0.00504739  0.01054983  0.00849543 -0.02326337 -0.0172851 ]
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Progress: 2.4% ... Training loss: 0.307 ... Validation loss: 0.475hidden_inputs = [ 0.09207972  0.26493903  0.58765913  0.49237986 -1.59651056 -0.43071485]
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Progress: 2.4% ... Training loss: 0.308 ... Validation loss: 0.499hidden_inputs = [-0.31043678 -0.63080881 -0.07815703 -0.66960524 -0.03911985  0.70067544]
hidden_outputs = [ 0.42300813  0.34732716  0.48047068  0.33858524  0.49022128  0.66833751]
final_inputs = [ 1.07460521]
final_outputs = [ 1.07460521]
error = [ 0.14122714]
output_error_term = [ 0.14122714]
hidden_error = [-0.14405079 -0.07169776 -0.16011529 -0.1302786   0.34647497  0.28248058]
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Progress: 2.4% ... Training loss: 0.291 ... Validation loss: 0.468hidden_inputs = [ 1.06918963 -0.43064305  0.27745957  0.309977   -0.67335032 -0.99673855]
hidden_outputs = [ 0.74444278  0.39397279  0.56892329  0.57687965  0.33774706  0.26958314]
final_inputs = [-0.87490822]
final_outputs = [-0.87490822]
error = [ 0.4699021]
output_error_term = [ 0.4699021]
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Progress: 2.4% ... Training loss: 0.292 ... Validation loss: 0.464hidden_inputs = [-0.01648032 -0.12338487 -0.61548063 -0.8351166  -0.83063219  0.55633774]
hidden_outputs = [ 0.49588001  0.46919286  0.35081001  0.30256428  0.30351141  0.63560474]
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final_outputs = [ 0.55148903]
error = [-1.24317406]
output_error_term = [-1.24317406]
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delta_weights_h_o = [[-3.70802784]
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self.weights_hidden_to_output = [[-1.0611432 ]
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self.weights_input_to_hidden = [[-0.20767421 -0.2963543  -0.35106761 -0.47051462  0.28160047  0.11458066]
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Progress: 2.4% ... Training loss: 0.290 ... Validation loss: 0.462hidden_inputs = [-0.56828082  0.06923141 -0.28652221 -0.2051114   1.00147807  0.63777159]
hidden_outputs = [ 0.36163361  0.51730094  0.4288555   0.44890117  0.73134909  0.65424955]
final_inputs = [ 1.48126433]
final_outputs = [ 1.48126433]
error = [ 0.51190893]
output_error_term = [ 0.51190893]
hidden_error = [-0.54320868 -0.27763123 -0.60081536 -0.4883539   1.25268666  1.00736518]
hidden_error_term = [-0.1254023  -0.06932471 -0.14716279 -0.12081334  0.24612487  0.22787313]
delta_weights_i_h = [[-0.75839008 -0.41743542 -0.7914527  -0.62953795  1.88653249  1.5134405 ]
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Progress: 2.5% ... Training loss: 0.290 ... Validation loss: 0.466hidden_inputs = [ 0.00411937 -0.08837836 -0.39640733  0.33220262 -0.09993445  0.00282303]
hidden_outputs = [ 0.50102984  0.47791978  0.40217582  0.58229521  0.47503716  0.50070576]
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final_outputs = [ 0.34097644]
error = [ 0.84177758]
output_error_term = [ 0.84177758]
hidden_error = [-0.88783708 -0.44903078 -0.98514824 -0.80133969  2.06036606  1.65871574]
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Progress: 2.5% ... Training loss: 0.290 ... Validation loss: 0.467hidden_inputs = [-0.37447152 -0.70058766 -0.8344659  -1.11987423  0.53435913  0.81440269]
hidden_outputs = [ 0.40746099  0.33168195  0.30270161  0.24603461  0.63049923  0.6930469 ]
final_inputs = [ 1.69676301]
final_outputs = [ 1.69676301]
error = [ 0.07588801]
output_error_term = [ 0.07588801]
hidden_error = [-0.08039995 -0.04060787 -0.08941633 -0.07257819  0.18494112  0.14906738]
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Progress: 2.5% ... Training loss: 0.291 ... Validation loss: 0.461hidden_inputs = [ 0.09046243 -0.00795913  0.19860359  0.76968121 -0.7548416  -0.39938535]
hidden_outputs = [ 0.5226002   0.49801023  0.54948834  0.68345193  0.31976726  0.40146003]
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error = [-0.09710608]
output_error_term = [-0.09710608]
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Progress: 2.5% ... Training loss: 0.292 ... Validation loss: 0.465hidden_inputs = [ 0.21151733 -0.30998281 -0.15809833 -0.31527255 -0.95104929 -0.53229667]
hidden_outputs = [ 0.55268306  0.42311893  0.46055754  0.42182829  0.27867385  0.36998139]
final_inputs = [-0.31088588]
final_outputs = [-0.31088588]
error = [-0.45798194]
output_error_term = [-0.45798194]
hidden_error = [ 0.47732542  0.23950592  0.53091064  0.43012883 -1.12492812 -0.90608992]
hidden_error_term = [ 0.11800654  0.05846083  0.13190172  0.10490377 -0.22612713 -0.21120517]
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Progress: 2.5% ... Training loss: 0.287 ... Validation loss: 0.458hidden_inputs = [-0.2275294  -0.24251042  0.01864224  0.35035496  0.0095746  -0.18443838]
hidden_outputs = [ 0.44336178  0.43966779  0.50466042  0.58670365  0.50239363  0.45402067]
final_inputs = [ 0.2639598]
final_outputs = [ 0.2639598]
error = [ 0.38402778]
output_error_term = [ 0.38402778]
hidden_error = [-0.40728784 -0.20533781 -0.45148912 -0.36745202  0.94035541  0.75597823]
hidden_error_term = [-0.10051543 -0.05058703 -0.11286247 -0.08910068  0.23508347  0.18739634]
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Progress: 2.5% ... Training loss: 0.289 ... Validation loss: 0.468hidden_inputs = [-0.60850658 -0.69740988 -0.1361021  -0.37934157  0.16610618  0.61276121]
hidden_outputs = [ 0.35239994  0.33238674  0.4660269   0.40628571  0.54143133  0.64857041]
final_inputs = [ 1.12434013]
final_outputs = [ 1.12434013]
error = [-1.28677178]
output_error_term = [-1.28677178]
hidden_error = [ 1.35654446  0.68580439  1.50475844  1.22517982 -3.15307352 -2.53577066]
hidden_error_term = [ 0.30958274  0.15218397  0.37445286  0.29553498 -0.78285596 -0.57797017]
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Progress: 2.5% ... Training loss: 0.291 ... Validation loss: 0.463hidden_inputs = [-0.2122411  -0.14305796 -0.17365983  0.4127471  -0.26636653 -0.14142765]
hidden_outputs = [ 0.44713801  0.46429638  0.45669382  0.6017464   0.43379932  0.4647019 ]
final_inputs = [ 0.15125099]
final_outputs = [ 0.15125099]
error = [-0.1317518]
output_error_term = [-0.1317518]
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Progress: 2.5% ... Training loss: 0.336 ... Validation loss: 0.475hidden_inputs = [-0.34361364 -0.43976214 -0.91867686 -0.15012225  1.3153589   0.65314797]
hidden_outputs = [ 0.41493195  0.39179765  0.28522757  0.46253976  0.78840851  0.6577195 ]
final_inputs = [ 1.94301082]
final_outputs = [ 1.94301082]
error = [ 0.07772772]
output_error_term = [ 0.07772772]
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Progress: 2.5% ... Training loss: 0.293 ... Validation loss: 0.462hidden_inputs = [ 0.66261354  0.52701317  0.25270341  0.03138877 -2.18703979 -0.67204059]
hidden_outputs = [ 0.65984724  0.62878621  0.56284179  0.50784655  0.10092037  0.33804007]
final_inputs = [-1.30005334]
final_outputs = [-1.30005334]
error = [ 0.382333]
output_error_term = [ 0.382333]
hidden_error = [-0.4075844  -0.20950376 -0.45474574 -0.37128186  0.93706675  0.75008331]
hidden_error_term = [-0.09148185 -0.04890113 -0.1118906  -0.0927976   0.08502517  0.16784538]
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Progress: 2.5% ... Training loss: 0.287 ... Validation loss: 0.462hidden_inputs = [-0.23385739 -0.27257146  0.51959442 -0.19404698 -0.79753571 -0.37222135]
hidden_outputs = [ 0.44180065  0.43227591  0.62705292  0.45163991  0.3105529   0.40800437]
final_inputs = [-0.25191696]
final_outputs = [-0.25191696]
error = [-0.08693248]
output_error_term = [-0.08693248]
hidden_error = [ 0.08998712  0.0451244   0.1002554   0.08180188 -0.214727   -0.17276563]
hidden_error_term = [ 0.02219198  0.01107413  0.02344548  0.02025916 -0.04597516 -0.04172926]
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delta_weights_h_o = [[-4.13695342]
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self.weights_hidden_to_output = [[-1.05453004]
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Progress: 2.5% ... Training loss: 0.289 ... Validation loss: 0.461hidden_inputs = [-0.27472796 -0.13894219  0.45104372 -0.5882761  -1.1198495  -0.05286717]
hidden_outputs = [ 0.43174676  0.46532023  0.61088736  0.35703049  0.2460392   0.48678628]
final_inputs = [-0.19929132]
final_outputs = [-0.19929132]
error = [ 0.39520831]
output_error_term = [ 0.39520831]
hidden_error = [-0.41675903 -0.21173306 -0.46222612 -0.37776466  0.96992461  0.77713482]
hidden_error_term = [-0.10224828 -0.05267862 -0.10987299 -0.08671955  0.17992481  0.19414802]
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Progress: 2.6% ... Training loss: 0.286 ... Validation loss: 0.456hidden_inputs = [ 0.25278394  0.17279282 -0.31594768 -0.56966052 -0.78211913  0.11013084]
hidden_outputs = [ 0.5628616   0.54309104  0.42166364  0.36131516  0.31386335  0.52750492]
final_inputs = [ 0.10917334]
final_outputs = [ 0.10917334]
error = [ 0.52227507]
output_error_term = [ 0.52227507]
hidden_error = [-0.54690079 -0.27754765 -0.60491894 -0.49118492  1.28704682  1.03159168]
hidden_error_term = [-0.13456407 -0.06887155 -0.1475176  -0.11334903  0.27716958  0.2571175 ]
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Progress: 2.6% ... Training loss: 0.301 ... Validation loss: 0.472hidden_inputs = [-0.05611325 -0.0306006   0.05792654 -0.11950178 -1.31325603 -0.11480524]
hidden_outputs = [ 0.48597537  0.49235045  0.51447759  0.47016006  0.2119425   0.47133017]
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output_error_term = [-0.18527986]
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delta_weights_h_o = [[ 9.63247023]
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self.weights_hidden_to_output = [[-1.02600733]
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self.weights_input_to_hidden = [[-0.19510273 -0.29153336 -0.33722177 -0.46288794  0.26200184  0.09695724]
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Progress: 2.6% ... Training loss: 0.290 ... Validation loss: 0.464hidden_inputs = [ 0.18074869 -0.52596536  0.22180327 -0.13573211 -1.10010101 -0.54223616]
hidden_outputs = [ 0.54506455  0.37145839  0.5552246   0.46611897  0.24972097  0.36766755]
final_inputs = [-0.46336377]
final_outputs = [-0.46336377]
error = [-0.399226]
output_error_term = [-0.399226]
hidden_error = [ 0.4096088   0.20359564  0.45448085  0.3676059  -0.98482991 -0.79326565]
hidden_error_term = [ 0.10157036  0.04753491  0.11223416  0.09147949 -0.18451813 -0.18442484]
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Progress: 2.6% ... Training loss: 0.288 ... Validation loss: 0.457hidden_inputs = [-0.43735073 -0.79514206 -0.08248913 -0.50512968 -0.42113573  0.18358632]
hidden_outputs = [ 0.39237242  0.31106564  0.4793894   0.37633593  0.39624501  0.5457681 ]
final_inputs = [ 0.59081661]
final_outputs = [ 0.59081661]
error = [-0.40041268]
output_error_term = [-0.40041268]
hidden_error = [ 0.41327716  0.20784202  0.45967698  0.37127802 -0.9866618  -0.79248173]
hidden_error_term = [ 0.09853201  0.04454134  0.11472398  0.08714162 -0.23604394 -0.1964604 ]
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Progress: 2.6% ... Training loss: 0.285 ... Validation loss: 0.462hidden_inputs = [-0.40667178 -0.1257507  -0.22375004 -0.07394356  0.36404292  0.28227515]
hidden_outputs = [ 0.39971043  0.46860369  0.4442947   0.48152253  0.59001876  0.57010392]
final_inputs = [ 0.95800627]
final_outputs = [ 0.95800627]
error = [ 0.48386138]
output_error_term = [ 0.48386138]
hidden_error = [-0.50285491 -0.25320012 -0.55923982 -0.45252704  1.19195865  0.95821195]
hidden_error_term = [-0.12065601 -0.06305044 -0.13807459 -0.11297726  0.28833077  0.2348438 ]
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Progress: 2.6% ... Training loss: 0.324 ... Validation loss: 0.495hidden_inputs = [-0.18699783 -0.07591149  0.02771969  0.41259751 -0.1638973  -0.15971724]
hidden_outputs = [ 0.4533863   0.48103123  0.50692948  0.60171055  0.45911715  0.46015536]
final_inputs = [ 0.06671781]
final_outputs = [ 0.06671781]
error = [-0.88520313]
output_error_term = [-0.88520313]
hidden_error = [ 0.947762    0.49065514  1.0532054   0.85914101 -2.14562565 -1.71799173]
hidden_error_term = [ 0.23488117  0.12248724  0.26325078  0.20589741 -0.5328202  -0.42677046]
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Progress: 2.6% ... Training loss: 0.287 ... Validation loss: 0.459hidden_inputs = [-0.25211367 -0.00681129  0.01905337 -0.10563068 -0.16410038  0.0897616 ]
hidden_outputs = [ 0.43730332  0.49829718  0.5047632   0.47361686  0.45906672  0.52242534]
final_inputs = [ 0.40489716]
final_outputs = [ 0.40489716]
error = [-0.30821518]
output_error_term = [-0.30821518]
hidden_error = [ 0.31957611  0.16238046  0.35685439  0.29033553 -0.75532494 -0.60554316]
hidden_error_term = [ 0.07863781  0.04059464  0.0892055   0.07238179 -0.18756566 -0.15108126]
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Progress: 2.6% ... Training loss: 0.287 ... Validation loss: 0.455hidden_inputs = [ 0.28352823  0.71496759  0.34136504 -0.30863525 -1.21659232  0.050843  ]
hidden_outputs = [ 0.570411    0.67149788  0.58452207  0.42344789  0.22853669  0.51270801]
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Progress: 2.6% ... Training loss: 0.293 ... Validation loss: 0.468hidden_inputs = [-0.38628146 -0.57445754 -0.37651396 -0.02897981  0.67004661  0.18483499]
hidden_outputs = [ 0.40461278  0.36020891  0.40696796  0.49275556  0.6615136   0.54607764]
final_inputs = [ 1.12167333]
final_outputs = [ 1.12167333]
error = [-0.51227714]
output_error_term = [-0.51227714]
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hidden_error_term = [ 0.1295511   0.06372034  0.14524082  0.12166038 -0.28073556 -0.2483715 ]
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Progress: 2.6% ... Training loss: 0.287 ... Validation loss: 0.465hidden_inputs = [-0.1864075  -0.58755592 -0.41452074 -0.58326392  0.74477863  0.904048  ]
hidden_outputs = [ 0.4535326   0.35719584  0.39782863  0.35818191  0.67803992  0.71178066]
final_inputs = [ 1.60628425]
final_outputs = [ 1.60628425]
error = [-0.20300799]
output_error_term = [-0.20300799]
hidden_error = [ 0.20995617  0.10736938  0.23586486  0.19131032 -0.49806101 -0.39944164]
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Progress: 2.7% ... Training loss: 0.286 ... Validation loss: 0.458hidden_inputs = [ 0.21141721  0.25870708  0.09184365 -0.32798679 -0.9413595   0.41855654]
hidden_outputs = [ 0.55265831  0.56431844  0.52294479  0.41873055  0.28062581  0.60313779]
final_inputs = [ 0.05056605]
final_outputs = [ 0.05056605]
error = [-0.53826801]
output_error_term = [-0.53826801]
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Progress: 2.7% ... Training loss: 0.288 ... Validation loss: 0.456hidden_inputs = [-0.80501966 -0.27668378 -0.58176526 -0.17621917  0.70497068  0.76360544]
hidden_outputs = [ 0.30895279  0.43126698  0.35852651  0.45605886  0.66928891  0.682136  ]
final_inputs = [ 1.64691281]
final_outputs = [ 1.64691281]
error = [ 0.45100851]
output_error_term = [ 0.45100851]
hidden_error = [-0.46094762 -0.23216846 -0.51787624 -0.41804371  1.12030359  0.89692885]
hidden_error_term = [-0.09841276 -0.0569453  -0.1191039  -0.10370376  0.24796941  0.19447792]
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Progress: 2.7% ... Training loss: 0.283 ... Validation loss: 0.466hidden_inputs = [ 0.17596425 -0.12081004 -0.06005663  0.50764742 -0.46952581 -0.19103564]
hidden_outputs = [ 0.5438779   0.46983417  0.48499035  0.62425481  0.38472848  0.45238581]
final_inputs = [-0.10196313]
final_outputs = [-0.10196313]
error = [ 0.39160207]
output_error_term = [ 0.39160207]
hidden_error = [-0.40246293 -0.20490485 -0.45111479 -0.36609515  0.96722308  0.77464353]
hidden_error_term = [-0.09984088 -0.05103975 -0.11267707 -0.08587155  0.22895377  0.19190468]
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Progress: 2.7% ... Training loss: 0.285 ... Validation loss: 0.458hidden_inputs = [ 0.62648077  0.01570638  0.62029537 -0.61511028 -1.4436368  -0.39297792]
hidden_outputs = [ 0.65169106  0.50392651  0.65028572  0.35089436  0.1909828   0.40300063]
final_inputs = [-0.72688583]
final_outputs = [-0.72688583]
error = [-0.25147812]
output_error_term = [-0.25147812]
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delta_weights_h_o = [[-1.40166159]
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self.weights_hidden_to_output = [[-1.03203633]
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Progress: 2.7% ... Training loss: 0.284 ... Validation loss: 0.458hidden_inputs = [-0.03795916 -0.16008374  0.24184438  0.23273579 -0.24015526 -0.16374011]
hidden_outputs = [ 0.49051135  0.46006431  0.56016812  0.55792273  0.44024809  0.45915619]
final_inputs = [ 0.0915774]
final_outputs = [ 0.0915774]
error = [-0.96519328]
output_error_term = [-0.96519328]
hidden_error = [ 0.99611454  0.50898303  1.11494379  0.90793318 -2.4067901  -1.92241357]
hidden_error_term = [ 0.24893895  0.126434    0.27469962  0.22393714 -0.59310458 -0.47739639]
delta_weights_i_h = [[  6.00672446e-01   3.37230698e-01   7.76255280e-01   4.46194101e-01
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Progress: 2.7% ... Training loss: 0.288 ... Validation loss: 0.470hidden_inputs = [ 0.15245589  0.23324629 -0.13267491 -0.38991666 -1.71604559 -0.45935847]
hidden_outputs = [ 0.53804032  0.55804864  0.46687984  0.40373736  0.15238122  0.38713802]
final_inputs = [-0.62260306]
final_outputs = [-0.62260306]
error = [-0.06356892]
output_error_term = [-0.06356892]
hidden_error = [ 0.06563117  0.03349636  0.07376263  0.05982933 -0.15791901 -0.12645707]
hidden_error_term = [ 0.01631282  0.00826122  0.01835974  0.01440292 -0.02039701 -0.03000348]
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Progress: 2.7% ... Training loss: 0.285 ... Validation loss: 0.456hidden_inputs = [-0.10991964  0.2886964   0.04294888 -0.25182086 -0.98814514 -0.32842086]
hidden_outputs = [ 0.47254772  0.57167696  0.51073557  0.43737537  0.2712786   0.4186249 ]
final_inputs = [-0.30690169]
final_outputs = [-0.30690169]
error = [-0.6163317]
output_error_term = [-0.6163317]
hidden_error = [ 0.64351963  0.3294597   0.72040389  0.58444652 -1.53237234 -1.22100619]
hidden_error_term = [ 0.16039493  0.0806723   0.18001794  0.14381952 -0.30292936 -0.29716616]
delta_weights_i_h = [[-1.15849237 -0.60897511 -1.22377215 -0.93320564  2.45770364  2.01308424]
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Progress: 2.7% ... Training loss: 0.284 ... Validation loss: 0.455hidden_inputs = [ 0.40028297  0.49449758  0.3627222   0.62244484 -3.29324595 -0.49810267]
hidden_outputs = [ 0.59875565  0.62116537  0.58969924  0.65077438  0.03580362  0.37798665]
final_inputs = [-1.38948392]
final_outputs = [-1.38948392]
error = [ 0.35047635]
output_error_term = [ 0.35047635]
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Progress: 2.7% ... Training loss: 0.293 ... Validation loss: 0.461hidden_inputs = [-0.03791636  0.14631101  0.17435409  0.38771161 -1.21469242 -0.61730618]
hidden_outputs = [ 0.49052205  0.53651264  0.54347844  0.5957317   0.22887183  0.35039437]
final_inputs = [-0.6600683]
final_outputs = [-0.6600683]
error = [-0.36791315]
output_error_term = [-0.36791315]
hidden_error = [ 0.37596913  0.18462959  0.42255124  0.33911578 -0.92594456 -0.74309505]
hidden_error_term = [ 0.09395851  0.04591125  0.10483903  0.0816711  -0.16341951 -0.16914192]
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Progress: 2.8% ... Training loss: 0.283 ... Validation loss: 0.457hidden_inputs = [ 0.5312295   0.24240099 -0.63994834 -0.87810085 -0.86532919  0.68183433]
hidden_outputs = [ 0.62976983  0.56030525  0.34525822  0.29357148  0.29622713  0.66414798]
final_inputs = [ 0.41981358]
final_outputs = [ 0.41981358]
error = [-0.43339272]
output_error_term = [-0.43339272]
hidden_error = [ 0.45406971  0.22960801  0.5095184   0.41030918 -1.07920484 -0.86311317]
hidden_error_term = [ 0.1058708   0.05656698  0.11517917  0.0850929  -0.22498897 -0.19252209]
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Progress: 2.8% ... Training loss: 0.285 ... Validation loss: 0.470hidden_inputs = [ 0.09662611  0.17372737  0.73344389 -0.2749788  -2.08295118 -0.17446086]
hidden_outputs = [ 0.52413775  0.54332294  0.67556056  0.43168522  0.11076495  0.45649507]
final_inputs = [-0.80668409]
final_outputs = [-0.80668409]
error = [ 0.08192071]
output_error_term = [ 0.08192071]
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Progress: 2.8% ... Training loss: 0.287 ... Validation loss: 0.456hidden_inputs = [ 0.13249132  0.04747607  0.15571559 -0.67408057 -0.1358991   0.53497208]
hidden_outputs = [ 0.53307446  0.51186679  0.53885043  0.33758373  0.46607742  0.63064202]
final_inputs = [ 0.68736072]
final_outputs = [ 0.68736072]
error = [-0.29297371]
output_error_term = [-0.29297371]
hidden_error = [ 0.30249578  0.15084012  0.34057876  0.27275663 -0.73615688 -0.59040557]
hidden_error_term = [ 0.07529304  0.03768879  0.08463064  0.0609941  -0.18319209 -0.13752474]
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delta_weights_h_o = [[-4.42833896]
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self.weights_hidden_to_output = [[-1.05325928]
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Progress: 2.8% ... Training loss: 0.287 ... Validation loss: 0.458hidden_inputs = [-0.37937852 -0.65192852 -0.46232345 -0.24286947 -0.65850428 -0.30186381]
hidden_outputs = [ 0.4062768   0.34255508  0.38643478  0.43957934  0.34107569  0.42510192]
final_inputs = [ 0.20850175]
final_outputs = [ 0.20850175]
error = [-0.06220227]
output_error_term = [-0.06220227]
hidden_error = [ 0.06551511  0.03329312  0.07374545  0.05932405 -0.15483898 -0.12409942]
hidden_error_term = [ 0.01580329  0.00749798  0.01748526  0.01461444 -0.03479899 -0.03032869]
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delta_weights_h_o = [[ 4.9144199 ]
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self.weights_hidden_to_output = [[-1.03022294]
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Progress: 2.8% ... Training loss: 0.287 ... Validation loss: 0.456hidden_inputs = [ 0.34760507  0.38686518 -0.05182018 -0.28810116 -1.80269133 -0.3420142 ]
hidden_outputs = [ 0.58603669  0.59552783  0.48704785  0.4284688   0.14152377  0.41532029]
final_inputs = [-0.68003487]
final_outputs = [-0.68003487]
error = [-0.07780683]
output_error_term = [-0.07780683]
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 [ 0.06133734 -0.12609341  0.13388259  0.10492137 -0.24150419  0.02591365]]
Progress: 2.8% ... Training loss: 0.305 ... Validation loss: 0.464hidden_inputs = [ 0.59431849 -0.63672981 -0.14173896  0.11189335 -0.4939601  -0.88088922]
hidden_outputs = [ 0.64435539  0.34598614  0.46462446  0.52794419  0.37896111  0.29299354]
final_inputs = [-0.44633194]
final_outputs = [-0.44633194]
error = [-0.42177088]
output_error_term = [-0.42177088]
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   -3.69502901e-01  -2.09942040e-01]
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Progress: 2.8% ... Training loss: 0.289 ... Validation loss: 0.469hidden_inputs = [-0.55791342 -0.84511338 -0.36453373 -0.10922843  0.76661524  0.4095256 ]
hidden_outputs = [ 0.36403039  0.30045894  0.40986252  0.47272001  0.68278825  0.60097412]
final_inputs = [ 1.41978728]
final_outputs = [ 1.41978728]
error = [ 1.99024139]
output_error_term = [ 1.99024139]
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hidden_error_term = [-0.48391159 -0.22252266 -0.56791717 -0.4720644   1.0726593   0.95001123]
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Progress: 2.8% ... Training loss: 0.316 ... Validation loss: 0.479hidden_inputs = [-0.06195754 -0.26815334 -0.0476229  -0.3377116   0.24535122  0.29299094]
hidden_outputs = [ 0.48451557  0.4333605   0.48809652  0.41636546  0.56103195  0.57272821]
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error = [-0.1438488]
output_error_term = [-0.1438488]
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delta_weights_h_o = [[-17.008713  ]
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self.weights_hidden_to_output = [[-1.08027662]
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self.weights_input_to_hidden = [[-0.1969532  -0.29420764 -0.33834429 -0.46813438  0.28222684  0.10737039]
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Progress: 2.8% ... Training loss: 0.346 ... Validation loss: 0.506hidden_inputs = [ 0.17242892  0.42521742  0.13287626 -0.53516383 -1.83731029 -0.14961642]
hidden_outputs = [ 0.54300074  0.60473106  0.53317027  0.36931331  0.13736971  0.46266551]
final_inputs = [-0.69500408]
final_outputs = [-0.69500408]
error = [ 0.10806711]
output_error_term = [ 0.10806711]
hidden_error = [-0.11674238 -0.06092268 -0.13119805 -0.1065336   0.26608028  0.21153458]
hidden_error_term = [-0.02896973 -0.01456243 -0.03265516 -0.02481391  0.03153032  0.05258879]
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Progress: 2.8% ... Training loss: 0.298 ... Validation loss: 0.466hidden_inputs = [ 0.99668941 -0.09489612  0.81465825 -0.20713517 -1.64013454 -1.14178134]
hidden_outputs = [ 0.73040718  0.47629376  0.69310126  0.44840057  0.16244676  0.24199345]
final_inputs = [-1.26764529]
final_outputs = [-1.26764529]
error = [ 0.41056857]
output_error_term = [ 0.41056857]
hidden_error = [-0.4139495  -0.20365766 -0.46667367 -0.37429162  1.03911339  0.83217674]
hidden_error_term = [-0.08151184 -0.05079996 -0.09926704 -0.09257635  0.14137949  0.15264836]
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Progress: 2.9% ... Training loss: 0.282 ... Validation loss: 0.456hidden_inputs = [-0.13276532  0.18263684  0.15958596 -1.13916048 -1.18969661 -0.00585977]
hidden_outputs = [ 0.46685734  0.54553271  0.53981203  0.24247453  0.2333132   0.49853506]
final_inputs = [-0.02112333]
final_outputs = [-0.02112333]
error = [ 0.87309399]
output_error_term = [ 0.87309399]
hidden_error = [-0.89944082 -0.44996761 -1.01234616 -0.81427277  2.20074641  1.75994403]
hidden_error_term = [-0.22387223 -0.11155902 -0.25148197 -0.14956614  0.39366545  0.43998223]
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Progress: 2.9% ... Training loss: 0.287 ... Validation loss: 0.458hidden_inputs = [ 0.02225766 -0.56810858  0.09781846 -0.64596255 -0.29033727  0.2347242 ]
hidden_outputs = [ 0.50556419  0.36167337  0.52443513  0.34389994  0.4279213   0.55841311]
final_inputs = [ 0.52038085]
final_outputs = [ 0.52038085]
error = [ 0.07798923]
output_error_term = [ 0.07798923]
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Progress: 2.9% ... Training loss: 0.282 ... Validation loss: 0.459hidden_inputs = [-0.57144853 -0.60735317 -0.18648303 -0.51089551  0.14733187  0.06819679]
hidden_outputs = [ 0.36090265  0.35266321  0.45351388  0.37498362  0.53676648  0.51704259]
final_inputs = [ 0.97993863]
final_outputs = [ 0.97993863]
error = [-0.40362077]
output_error_term = [-0.40362077]
hidden_error = [ 0.41235811  0.20697115  0.46397458  0.37209188 -1.0188876  -0.81304401]
hidden_error_term = [ 0.09511119  0.04724983  0.11499101  0.08720751 -0.25334459 -0.20302485]
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Progress: 2.9% ... Training loss: 0.288 ... Validation loss: 0.469hidden_inputs = [ 0.20937448  0.29722428  0.09054191 -0.19693939 -1.49876077  0.05747677]
hidden_outputs = [ 0.55215324  0.57376383  0.52262003  0.45092367  0.18261042  0.51436524]
final_inputs = [-0.44582864]
final_outputs = [-0.44582864]
error = [-0.25688251]
output_error_term = [-0.25688251]
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hidden_error_term = [ 0.06639214  0.03363039  0.07508347  0.06016431 -0.09580818 -0.12736568]
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Progress: 2.9% ... Training loss: 0.281 ... Validation loss: 0.462hidden_inputs = [ 0.54587844  0.02192356  0.39361091  0.25234543 -1.21443298 -0.71805706]
hidden_outputs = [ 0.63317883  0.50548067  0.59715165  0.56275371  0.22891763  0.32782097]
final_inputs = [-0.88067744]
final_outputs = [-0.88067744]
error = [ 0.13386184]
output_error_term = [ 0.13386184]
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Progress: 2.9% ... Training loss: 0.288 ... Validation loss: 0.471hidden_inputs = [-0.26094823  0.12188415 -0.11604201 -0.31577403 -0.97008704  0.23618395]
hidden_outputs = [ 0.43513063  0.53043337  0.47102201  0.42170599  0.27486315  0.55877303]
final_inputs = [ 0.11384583]
final_outputs = [ 0.11384583]
error = [-0.05024218]
output_error_term = [-0.05024218]
hidden_error = [ 0.05233145  0.02673742  0.05868837  0.04730663 -0.1255397  -0.09979019]
hidden_error_term = [ 0.01286265  0.00665959  0.01462281  0.01153667 -0.02502174 -0.02460285]
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delta_weights_h_o = [[ 4.84434466]
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self.weights_hidden_to_output = [[-1.01887607]
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Progress: 2.9% ... Training loss: 0.285 ... Validation loss: 0.459hidden_inputs = [ 0.97782128 -0.19347845  0.152072    0.26695443 -1.07770902 -0.87153996]
hidden_outputs = [ 0.7266757   0.45178071  0.5379449   0.56634507  0.25393981  0.29493397]
final_inputs = [-0.86502477]
final_outputs = [-0.86502477]
error = [-0.16295669]
output_error_term = [-0.16295669]
hidden_error = [ 0.16603267  0.08276006  0.18619514  0.14913251 -0.41274369 -0.32851714]
hidden_error_term = [ 0.0329771   0.02049759  0.0462807   0.0366267  -0.0781961  -0.06831446]
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delta_weights_h_o = [[-7.38481438]
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self.weights_hidden_to_output = [[-1.05349239]
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Progress: 2.9% ... Training loss: 0.297 ... Validation loss: 0.477hidden_inputs = [-0.45679588 -0.40217925 -0.69209657 -0.44960145  1.70820264  0.83955106]
hidden_outputs = [ 0.3877462   0.40078886  0.33356684  0.38945553  0.84660301  0.69837066]
final_inputs = [ 2.11065456]
final_outputs = [ 2.11065456]
error = [-0.42621244]
output_error_term = [-0.42621244]
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Progress: 2.9% ... Training loss: 0.280 ... Validation loss: 0.462hidden_inputs = [ 0.44987551  0.79716795  1.08270084 -0.31941803 -2.21891315 -0.39669683]
hidden_outputs = [ 0.61060964  0.68936835  0.74700475  0.42081759  0.09806489  0.40210622]
final_inputs = [-1.17098792]
final_outputs = [-1.17098792]
error = [ 0.15403258]
output_error_term = [ 0.15403258]
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   -1.20764645e-01  -1.86734199e-01]
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Progress: 2.9% ... Training loss: 0.280 ... Validation loss: 0.457hidden_inputs = [ 0.13057055 -0.37577954  0.6532713  -0.31000275 -1.68111036 -0.5673075 ]
hidden_outputs = [ 0.53259634  0.40714522  0.65774726  0.42311407  0.1569485   0.36185834]
final_inputs = [-0.77903596]
final_outputs = [-0.77903596]
error = [-0.25445855]
output_error_term = [-0.25445855]
hidden_error = [ 0.26269672  0.13168698  0.29247559  0.2354705  -0.6459797  -0.51377849]
hidden_error_term = [ 0.06539506  0.03178634  0.06584088  0.05747565 -0.08547323 -0.11864013]
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delta_weights_h_o = [[-2.38618468]
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self.weights_hidden_to_output = [[-1.04356052]
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Progress: 3.0% ... Training loss: 0.280 ... Validation loss: 0.461hidden_inputs = [-0.35428947 -0.51768194 -0.31958691 -0.51236458  0.06063343 -0.19591445]
hidden_outputs = [ 0.41234262  0.37339443  0.42077642  0.37463938  0.51515371  0.45117745]
final_inputs = [ 0.74380386]
final_outputs = [ 0.74380386]
error = [ 0.46651544]
output_error_term = [ 0.46651544]
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delta_weights_h_o = [[-0.71068603]
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self.weights_hidden_to_output = [[-1.04689186]
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   -1.24220788e-01  -1.90191394e-01]
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Progress: 3.0% ... Training loss: 0.287 ... Validation loss: 0.471hidden_inputs = [ 0.65547955 -0.05663976  0.52127999 -0.10881362 -1.96901251 -0.73426024]
hidden_outputs = [ 0.6582442   0.48584385  0.62744702  0.47282341  0.12249499  0.32426054]
final_inputs = [-1.17207156]
final_outputs = [-1.17207156]
error = [ 0.26537734]
output_error_term = [ 0.26537734]
hidden_error = [-0.27782138 -0.14197475 -0.31141228 -0.2513194   0.67126956  0.53292911]
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Progress: 3.0% ... Training loss: 0.281 ... Validation loss: 0.463hidden_inputs = [ 0.5981003  -0.64415096 -0.15191614  0.26337991 -1.00802145 -0.27292501]
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error = [ 0.15106887]
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Progress: 3.0% ... Training loss: 0.279 ... Validation loss: 0.455hidden_inputs = [-0.2682683   0.23896803  0.5518746   0.16371195  0.08347567 -0.18790811]
hidden_outputs = [ 0.43333227  0.55945932  0.6345704   0.54083682  0.52085681  0.45316072]
final_inputs = [ 0.26189734]
final_outputs = [ 0.26189734]
error = [-0.39125066]
output_error_term = [-0.39125066]
hidden_error = [ 0.40527843  0.20417487  0.45399289  0.36554158 -0.99843679 -0.79014234]
hidden_error_term = [ 0.09951831  0.05032188  0.10527678  0.0907758  -0.24917487 -0.19580208]
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Progress: 3.0% ... Training loss: 0.312 ... Validation loss: 0.491hidden_inputs = [-0.59343767 -0.65250126 -0.41668755 -0.31579322  0.26894382  0.0437289 ]
hidden_outputs = [ 0.35584648  0.34242611  0.39730966  0.42170131  0.5668336   0.51093048]
final_inputs = [ 1.00394705]
final_outputs = [ 1.00394705]
error = [ 0.47099894]
output_error_term = [ 0.47099894]
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hidden_error_term = [-0.11447718 -0.05784576 -0.13459733 -0.11060336  0.29170936  0.23460311]
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Progress: 3.0% ... Training loss: 0.282 ... Validation loss: 0.464hidden_inputs = [ 0.18145363  0.72692377  0.03094527 -0.32291817 -1.77865398 -0.58710763]
hidden_outputs = [ 0.54523935  0.67412985  0.5077357   0.41996473  0.14446942  0.35729877]
final_inputs = [-0.76866472]
final_outputs = [-0.76866472]
error = [-0.2262384]
output_error_term = [-0.2262384]
hidden_error = [ 0.22985676  0.11406436  0.26008111  0.20803936 -0.57769118 -0.45979058]
hidden_error_term = [ 0.05699376  0.02505752  0.06500471  0.05067721 -0.07140148 -0.10558463]
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Progress: 3.0% ... Training loss: 0.283 ... Validation loss: 0.461hidden_inputs = [ 0.15031892  0.28995643  0.19064657  0.34710499  0.25866245 -0.53728382]
hidden_outputs = [ 0.53750913  0.57198547  0.54751781  0.58591537  0.56430746  0.36881966]
final_inputs = [ 0.15136723]
final_outputs = [ 0.15136723]
error = [ 1.24639598]
output_error_term = [ 1.24639598]
hidden_error = [-1.28766077 -0.65042368 -1.45389595 -1.16407422  3.18898609  2.52519093]
hidden_error_term = [-0.32010354 -0.15923549 -0.36019118 -0.282426    0.78405863  0.58784354]
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Progress: 3.0% ... Training loss: 0.297 ... Validation loss: 0.476hidden_inputs = [ 0.05164645  0.30360183  0.72318332 -0.07451445 -0.41381336 -0.57893517]
hidden_outputs = [ 0.51290874  0.57532278  0.67330762  0.48138     0.3979981   0.35917765]
final_inputs = [-0.38481628]
final_outputs = [-0.38481628]
error = [ 1.33050889]
output_error_term = [ 1.33050889]
hidden_error = [-1.4059688  -0.72181605 -1.58272466 -1.27021429  3.38139238  2.66090616]
hidden_error_term = [-0.35125792 -0.17635877 -0.34814319 -0.31711318  0.81016678  0.61245828]
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delta_weights_h_o = [[ 11.64875572]
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self.weights_hidden_to_output = [[-1.00211154]
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Progress: 3.0% ... Training loss: 0.308 ... Validation loss: 0.453hidden_inputs = [-0.02009335 -0.04900235  0.32592043 -0.35907535 -0.32004902 -0.2589281 ]
hidden_outputs = [ 0.49497683  0.48775186  0.58076643  0.41118342  0.4206638   0.43562722]
final_inputs = [ 0.22148937]
final_outputs = [ 0.22148937]
error = [ 0.16187152]
output_error_term = [ 0.16187152]
hidden_error = [-0.16221332 -0.07994979 -0.18406786 -0.14620981  0.42093275  0.33305684]
hidden_error_term = [-0.04054924 -0.01997545 -0.04481625 -0.03539909  0.10258374  0.08188407]
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Progress: 3.0% ... Training loss: 0.279 ... Validation loss: 0.454hidden_inputs = [ 0.14661061 -0.15340014  0.17505893  0.59226532 -1.45334282 -0.64775614]
hidden_outputs = [ 0.53658714  0.46172499  0.54365331  0.64388475  0.18948764  0.34349537]
final_inputs = [-0.85358767]
final_outputs = [-0.85358767]
error = [-0.04759349]
output_error_term = [-0.04759349]
hidden_error = [ 0.04901966  0.02463711  0.05569127  0.04477436 -0.12214079 -0.09611709]
hidden_error_term = [ 0.0121893   0.00612319  0.01381669  0.01026663 -0.01875864 -0.02167501]
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delta_weights_h_o = [[ 1.3519091 ]
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self.weights_hidden_to_output = [[-1.02362868]
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Progress: 3.0% ... Training loss: 0.277 ... Validation loss: 0.452hidden_inputs = [ 0.52855466  0.03629248  0.27948337  0.25120697 -1.53380631 -0.59476305]
hidden_outputs = [ 0.62914595  0.50907212  0.56941956  0.56247356  0.17743746  0.35554274]
final_inputs = [-0.91373709]
final_outputs = [-0.91373709]
error = [-0.03706158]
output_error_term = [-0.03706158]
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Progress: 3.1% ... Training loss: 0.281 ... Validation loss: 0.458hidden_inputs = [-0.00341289 -0.23029103  0.21592216 -0.61071639 -1.24907361 -0.1244491 ]
hidden_outputs = [ 0.49914678  0.44268034  0.55377179  0.3518958   0.22286054  0.46892782]
final_inputs = [-0.20928672]
final_outputs = [-0.20928672]
error = [ 0.7084218]
output_error_term = [ 0.7084218]
hidden_error = [-0.73176882 -0.36579756 -0.8299618  -0.672751    1.81527806  1.43033099]
hidden_error_term = [-0.18294167 -0.09024755 -0.2050907  -0.15343106  0.31439476  0.35620179]
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Progress: 3.1% ... Training loss: 0.279 ... Validation loss: 0.462hidden_inputs = [ 0.43788107  0.51861831  0.16655178  0.19094122 -2.82863801 -0.773341  ]
hidden_outputs = [ 0.60775402  0.62682462  0.54154196  0.5475908   0.05579611  0.31575682]
final_inputs = [-1.28445571]
final_outputs = [-1.28445571]
error = [ 0.27301343]
output_error_term = [ 0.27301343]
hidden_error = [-0.2775496  -0.13752228 -0.31453824 -0.25555039  0.7027411   0.55508876]
hidden_error_term = [-0.06616479 -0.0321686  -0.07809175 -0.06330881  0.03702244  0.1199294 ]
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   -1.65221789e-01  -8.00139604e-02]
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   -1.17451043e-01  -1.73534018e-01]
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   -3.08231319e-01  -1.45160284e-01]
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Progress: 3.1% ... Training loss: 0.280 ... Validation loss: 0.466hidden_inputs = [ 0.58732779  0.294932    0.51168017  0.58397242 -1.30003884 -0.43752822]
hidden_outputs = [ 0.64275178  0.57320314  0.62520026  0.64198095  0.21415848  0.3923301 ]
final_inputs = [-0.91555702]
final_outputs = [-0.91555702]
error = [-0.08485915]
output_error_term = [-0.08485915]
hidden_error = [ 0.08665113  0.04273832  0.09788603  0.07963578 -0.21894724 -0.17315297]
hidden_error_term = [ 0.019897    0.01045556  0.02293713  0.0183036  -0.03684764 -0.04128091]
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delta_weights_h_o = [[-4.92823557]
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self.weights_hidden_to_output = [[-1.04421813]
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Progress: 3.1% ... Training loss: 0.285 ... Validation loss: 0.461hidden_inputs = [ 0.14406995 -0.32943713  0.13225632  0.28493752 -0.05187734 -0.30462464]
hidden_outputs = [ 0.53595532  0.41837759  0.53301597  0.57075631  0.48703357  0.42442734]
final_inputs = [ 0.16276636]
final_outputs = [ 0.16276636]
error = [ 0.88767432]
output_error_term = [ 0.88767432]
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Progress: 3.1% ... Training loss: 0.283 ... Validation loss: 0.464hidden_inputs = [-0.18926355 -0.20763219  0.32392818 -0.02933232 -0.23027347 -0.0379703 ]
hidden_outputs = [ 0.45282485  0.44827764  0.58028128  0.49266745  0.44268467  0.49050857]
final_inputs = [ 0.34933183]
final_outputs = [ 0.34933183]
error = [-0.53932877]
output_error_term = [-0.53932877]
hidden_error = [ 0.54982484  0.26795485  0.61697747  0.50027082 -1.40107548 -1.10446635]
hidden_error_term = [ 0.13623258  0.06627188  0.1502679   0.12504081 -0.34566627 -0.27601709]
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delta_weights_h_o = [[-9.50821819]
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self.weights_hidden_to_output = [[-1.06403115]
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Progress: 3.1% ... Training loss: 0.302 ... Validation loss: 0.465hidden_inputs = [ 0.12751582  0.02340253  0.52982605 -0.23593462 -0.62114015 -0.90558303]
hidden_outputs = [ 0.53183583  0.50585036  0.62944254  0.44128844  0.34952219  0.28790454]
final_inputs = [-0.5441611]
final_outputs = [-0.5441611]
error = [-0.03174976]
output_error_term = [-0.03174976]
hidden_error = [ 0.03378273  0.01711004  0.03780367  0.03088317 -0.08140089 -0.06362251]
hidden_error_term = [ 0.00841144  0.00427692  0.0088175   0.00761434 -0.01850702 -0.0130436 ]
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Progress: 3.1% ... Training loss: 0.279 ... Validation loss: 0.458hidden_inputs = [ 0.49078514 -0.33792226  0.25977084 -0.38887349 -1.08695515 -0.42906354]
hidden_outputs = [ 0.62029137  0.41631427  0.56457996  0.40398852  0.25219208  0.39434997]
final_inputs = [-0.40586465]
final_outputs = [-0.40586465]
error = [-0.01568064]
output_error_term = [-0.01568064]
hidden_error = [ 0.01597399  0.00784569  0.01795454  0.01467195 -0.04061856 -0.03202986]
hidden_error_term = [ 0.00376235  0.00190648  0.00441375  0.00353274 -0.00766031 -0.00764995]
delta_weights_i_h = [[ 0.77615358  0.31453154  0.73266306  0.49600298 -1.301255   -1.16516115]
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Progress: 3.1% ... Training loss: 0.281 ... Validation loss: 0.457hidden_inputs = [-0.09053549 -0.10968933  0.26341659 -0.46253817 -0.68113243 -0.00072057]
hidden_outputs = [ 0.47738158  0.47260513  0.56547598  0.38638387  0.3360086   0.49981986]
final_inputs = [ 0.11267129]
final_outputs = [ 0.11267129]
error = [-0.44049462]
output_error_term = [-0.44049462]
hidden_error = [ 0.45765761  0.22811422  0.51277144  0.41816247 -1.13656914 -0.8914222 ]
hidden_error_term = [ 0.11418027  0.05685736  0.12599456  0.09914272 -0.25357633 -0.22285552]
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Progress: 3.1% ... Training loss: 0.276 ... Validation loss: 0.450hidden_inputs = [-0.1358173  -0.67178503 -0.18006964  0.2411231  -1.03796299 -0.22098948]
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final_inputs = [-0.12490051]
final_outputs = [-0.12490051]
error = [ 0.29876527]
output_error_term = [ 0.29876527]
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Progress: 3.1% ... Training loss: 0.280 ... Validation loss: 0.447hidden_inputs = [ 0.36382339  0.153564    0.21256692 -0.1243733  -0.9043987  -0.54246346]
hidden_outputs = [ 0.58996565  0.53831573  0.55294253  0.4689467   0.2881474   0.36761471]
final_inputs = [-0.50613911]
final_outputs = [-0.50613911]
error = [-0.04771952]
output_error_term = [-0.04771952]
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delta_weights_h_o = [[ 4.8353859 ]
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Progress: 3.2% ... Training loss: 0.278 ... Validation loss: 0.456hidden_inputs = [-0.33928572  0.04714848  0.12745751 -0.66524324  0.18438562 -0.22800289]
hidden_outputs = [ 0.415983    0.51178494  0.53182131  0.33956277  0.54596625  0.44324493]
final_inputs = [ 0.71294427]
final_outputs = [ 0.71294427]
error = [-0.59421007]
output_error_term = [-0.59421007]
hidden_error = [ 0.60882761  0.30117316  0.68158405  0.55396817 -1.54796543 -1.21036353]
hidden_error_term = [ 0.14790928  0.07525146  0.16970584  0.12423284 -0.38372067 -0.29869213]
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delta_weights_h_o = [[-4.58017417]
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self.weights_hidden_to_output = [[-1.04606953]
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Progress: 3.2% ... Training loss: 0.277 ... Validation loss: 0.450hidden_inputs = [ 0.52515163 -0.61153978  0.28641983  0.0680244  -1.31297464 -0.87250291]
hidden_outputs = [ 0.6283516   0.35170803  0.57111942  0.51699954  0.21198951  0.29473377]
final_inputs = [-0.85334374]
final_outputs = [-0.85334374]
error = [ 0.52552041]
output_error_term = [ 0.52552041]
hidden_error = [-0.54973088 -0.2766131  -0.61230324 -0.49885337  1.36383695  1.06112002]
hidden_error_term = [-0.12837638 -0.06307041 -0.1499788  -0.12456918  0.2278289   0.22057053]
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delta_weights_h_o = [[ 1.16439945]
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self.weights_hidden_to_output = [[-1.04061141]
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Progress: 3.2% ... Training loss: 0.278 ... Validation loss: 0.448hidden_inputs = [-0.14782146 -0.36542322 -0.23108587  0.1157813  -0.79085528 -0.80029177]
hidden_outputs = [ 0.46311178  0.40964739  0.44248425  0.52891303  0.31198505  0.30996311]
final_inputs = [-0.26818829]
final_outputs = [-0.26818829]
error = [-0.74876705]
output_error_term = [-0.74876705]
hidden_error = [ 0.77917553  0.39442144  0.86794043  0.70659245 -1.95292924 -1.51663117]
hidden_error_term = [ 0.19373363  0.09538546  0.21411391  0.17605743 -0.419197   -0.32438615]
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delta_weights_h_o = [[ 2.23777539]
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Progress: 3.2% ... Training loss: 0.279 ... Validation loss: 0.455hidden_inputs = [-0.24010869 -0.48158356  0.02211341 -0.00597751 -0.47169118 -0.17516057]
hidden_outputs = [ 0.44025957  0.38187826  0.50552813  0.49850563  0.38421604  0.45632148]
final_inputs = [ 0.23479617]
final_outputs = [ 0.23479617]
error = [-0.12157502]
output_error_term = [-0.12157502]
hidden_error = [ 0.12523709  0.06264448  0.14047796  0.11383988 -0.31810085 -0.24796262]
hidden_error_term = [ 0.03086231  0.01478706  0.0351152   0.02845972 -0.07526078 -0.06151759]
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delta_weights_h_o = [[-2.38563156]
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self.weights_hidden_to_output = [[-1.04130448]
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self.weights_input_to_hidden = [[ -1.89188365e-01  -2.93334220e-01  -3.36072771e-01  -4.68369911e-01
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Progress: 3.2% ... Training loss: 0.277 ... Validation loss: 0.454hidden_inputs = [ 0.43030572  0.01856045  0.61178099  0.21379143 -2.54365299 -0.90012164]
hidden_outputs = [ 0.60594667  0.50463998  0.64834696  0.55324521  0.07285404  0.2890255 ]
final_inputs = [-1.40379069]
final_outputs = [-1.40379069]
error = [ 0.38683535]
output_error_term = [ 0.38683535]
hidden_error = [-0.40281339 -0.2035325  -0.45229753 -0.36878738  1.00702231  0.78770949]
hidden_error_term = [-0.09618189 -0.05087874 -0.10312075 -0.09115131  0.06802066  0.16186623]
delta_weights_i_h = [[  1.06358796e+00   5.40441683e-01   1.30141976e+00   8.90933460e-01
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Progress: 3.2% ... Training loss: 0.280 ... Validation loss: 0.453hidden_inputs = [ 0.26912592  0.27680923  0.39029345  0.30584274 -1.24063565 -0.79366488]
hidden_outputs = [ 0.56687831  0.56876379  0.59635334  0.5758702   0.22432536  0.31138229]
final_inputs = [-0.92045867]
final_outputs = [-0.92045867]
error = [-0.0799575]
output_error_term = [-0.0799575]
hidden_error = [ 0.08317248  0.04200016  0.09372143  0.07642886 -0.20831623 -0.16254247]
hidden_error_term = [ 0.02042111  0.01030144  0.02256025  0.01866727 -0.03624775 -0.0348529 ]
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self.weights_hidden_to_output = [[-1.0329247 ]
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Progress: 3.2% ... Training loss: 0.276 ... Validation loss: 0.448hidden_inputs = [ 0.17540571 -0.70958588 -0.30292942  0.18301542  1.3727191  -0.14189802]
hidden_outputs = [ 0.54373934  0.32969035  0.42484152  0.54562657  0.79781911  0.4645849 ]
final_inputs = [ 1.27804591]
final_outputs = [ 1.27804591]
error = [-1.20341615]
output_error_term = [-1.20341615]
hidden_error = [ 1.24303827  0.62930103  1.40466562  1.14596677 -3.14120724 -2.44799048]
hidden_error_term = [ 0.30838147  0.13907214  0.34323173  0.28410604 -0.5066886  -0.60892728]
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Progress: 3.2% ... Training loss: 0.279 ... Validation loss: 0.453hidden_inputs = [-0.07519882 -0.62318911  0.47349876  0.07731914 -0.96821065 -0.1971436 ]
hidden_outputs = [ 0.48120915  0.34905649  0.61621153  0.51932016  0.2752373   0.45087311]
final_inputs = [-0.2691141]
final_outputs = [-0.2691141]
error = [ 0.02398661]
output_error_term = [ 0.02398661]
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hidden_error_term = [-0.00622492 -0.00285632 -0.0066469  -0.00573969  0.01246143  0.01207963]
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Progress: 3.2% ... Training loss: 0.277 ... Validation loss: 0.457hidden_inputs = [ 0.32889615 -0.26442253  0.36197653 -0.27217082 -2.28683327 -0.52966112]
hidden_outputs = [ 0.58149077  0.43427687  0.58951881  0.43237424  0.09221931  0.37059593]
final_inputs = [-0.89360783]
final_outputs = [-0.89360783]
error = [-0.01308639]
output_error_term = [-0.01308639]
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Progress: 3.2% ... Training loss: 0.279 ... Validation loss: 0.454hidden_inputs = [ 0.61277257 -0.26961708  0.16722831  0.88163266 -1.60951628 -0.8675742 ]
hidden_outputs = [ 0.648573    0.4330011   0.54170992  0.70716043  0.16665578  0.29575931]
final_inputs = [-1.11307328]
final_outputs = [-1.11307328]
error = [ 0.11265711]
output_error_term = [ 0.11265711]
hidden_error = [-0.11461958 -0.05703322 -0.12867752 -0.10516287  0.29581755  0.23131037]
hidden_error_term = [-0.02612479 -0.01400229 -0.03194552 -0.02177761  0.04108362  0.04817865]
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Progress: 3.3% ... Training loss: 0.279 ... Validation loss: 0.464hidden_inputs = [ 0.21707765 -0.64858152  0.32813319  0.44872806 -0.84389044 -0.65355907]
hidden_outputs = [ 0.5540573   0.34330926  0.58130508  0.61033678  0.30071605  0.34218796]
final_inputs = [-0.49148923]
final_outputs = [-0.49148923]
error = [-0.53097916]
output_error_term = [-0.53097916]
hidden_error = [ 0.54256203  0.27046934  0.60796573  0.49782511 -1.38863323 -1.0876034 ]
hidden_error_term = [ 0.13405504  0.06097677  0.14797246  0.11839565 -0.29201    -0.24481448]
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Progress: 3.3% ... Training loss: 0.279 ... Validation loss: 0.463hidden_inputs = [ 0.69006719  0.24931307  0.32461332 -0.07764546 -2.32109556 -0.21615462]
hidden_outputs = [ 0.66598187  0.56200742  0.58044814  0.48059838  0.08939084  0.44617077]
final_inputs = [-0.93269871]
final_outputs = [-0.93269871]
error = [-0.08425663]
output_error_term = [-0.08425663]
hidden_error = [ 0.08614909  0.04264614  0.09663698  0.07923998 -0.22079704 -0.1730128 ]
hidden_error_term = [ 0.01916387  0.01049756  0.02353382  0.01978017 -0.01797291 -0.04275188]
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delta_weights_h_o = [[-6.28411741]
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self.weights_hidden_to_output = [[-1.05191743]
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   -3.34480087e-01  -1.76382205e-01]
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   -1.23853435e-01  -1.71149906e-01]
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Progress: 3.3% ... Training loss: 0.291 ... Validation loss: 0.478hidden_inputs = [ 0.31546219 -0.39607711  0.5419574   0.704532   -1.1355887  -0.94310411]
hidden_outputs = [ 0.57821796  0.40225522  0.63226764  0.66919181  0.2431312   0.28027375]
final_inputs = [-1.02373837]
final_outputs = [-1.02373837]
error = [ 0.1115311]
output_error_term = [ 0.1115311]
hidden_error = [-0.1173215  -0.0597244  -0.1321467  -0.10788206  0.28943984  0.22498436]
hidden_error_term = [-0.0286126  -0.01436049 -0.0307248  -0.0238823   0.05326226  0.04538393]
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Progress: 3.3% ... Training loss: 0.282 ... Validation loss: 0.456hidden_inputs = [-0.56986373 -0.81891427 -0.42860583 -0.29217508  1.20680978  0.62232149]
hidden_outputs = [ 0.36126827  0.30599418  0.3944593   0.42747145  0.76973399  0.65074635]
final_inputs = [ 2.00261639]
final_outputs = [ 2.00261639]
error = [-2.15402193]
output_error_term = [-2.15402193]
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self.weights_hidden_to_output = [[-1.03031748]
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Progress: 3.3% ... Training loss: 0.275 ... Validation loss: 0.450hidden_inputs = [-0.33910962 -0.40459648 -0.28089609 -0.59651371  0.44416789 -0.25935978]
hidden_outputs = [ 0.41602578  0.40020849  0.4302341   0.35514171  0.60925171  0.4355211 ]
final_inputs = [ 1.02414841]
final_outputs = [ 1.02414841]
error = [-0.32654332]
output_error_term = [-0.32654332]
hidden_error = [ 0.33644329  0.16678442  0.38000947  0.30902529 -0.85904114 -0.66819946]
hidden_error_term = [ 0.08173833  0.04003521  0.09315275  0.07077176 -0.20450682 -0.16427181]
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Progress: 3.3% ... Training loss: 0.276 ... Validation loss: 0.454hidden_inputs = [-0.15659967 -0.46395115 -0.23251924 -0.06454691  0.51884402  0.19685746]
hidden_outputs = [ 0.4609299   0.38604892  0.44213068  0.48386887  0.62687742  0.54905605]
final_inputs = [ 1.12597413]
final_outputs = [ 1.12597413]
error = [ 0.36551103]
output_error_term = [ 0.36551103]
hidden_error = [-0.37616382 -0.18579464 -0.42491772 -0.3467352   0.96022656  0.74740298]
hidden_error_term = [-0.09346675 -0.04403614 -0.10480644 -0.08659358  0.22459903  0.18505212]
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Progress: 3.3% ... Training loss: 0.275 ... Validation loss: 0.455hidden_inputs = [ 0.6281143   0.20370754  0.05607072 -0.53861772 -2.87497605  0.18731973]
hidden_outputs = [ 0.65206176  0.5507515   0.51401401  0.36850919  0.05340454  0.54669348]
final_inputs = [-0.6421223]
final_outputs = [-0.6421223]
error = [-0.16533691]
output_error_term = [-0.16533691]
hidden_error = [ 0.17012618  0.0844558   0.19256698  0.1569341  -0.43422294 -0.33822377]
hidden_error_term = [ 0.03859776  0.02089641  0.04810393  0.03652016 -0.02195105 -0.08381852]
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Progress: 3.3% ... Training loss: 0.279 ... Validation loss: 0.445hidden_inputs = [-0.30609327 -0.46387661  0.3047593  -0.57606848 -0.84696224 -0.1155674 ]
hidden_outputs = [ 0.42406861  0.38606659  0.57560555  0.35983774  0.30007049  0.47114026]
final_inputs = [ 0.1100678]
final_outputs = [ 0.1100678]
error = [-0.3551953]
output_error_term = [-0.3551953]
hidden_error = [ 0.36559915  0.18365572  0.41180155  0.33509516 -0.93844986 -0.72388647]
hidden_error_term = [ 0.0892919   0.04352993  0.10059645  0.07719069 -0.19710092 -0.1803687 ]
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Progress: 3.3% ... Training loss: 0.283 ... Validation loss: 0.468hidden_inputs = [ 0.41884771  0.30064662  0.48953397 -0.98139196 -1.20134474 -0.24740736]
hidden_outputs = [ 0.60320748  0.57460058  0.61999664  0.27261568  0.23123608  0.43846174]
final_inputs = [-0.44196885]
final_outputs = [-0.44196885]
error = [-0.12842895]
output_error_term = [-0.12842895]
hidden_error = [ 0.13460804  0.06881244  0.15169965  0.12298605 -0.33722723 -0.25903456]
hidden_error_term = [ 0.03221819  0.01682015  0.03574056  0.02438769 -0.05994752 -0.06377769]
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Progress: 3.4% ... Training loss: 0.280 ... Validation loss: 0.448hidden_inputs = [ 0.02458086  0.08186013  0.40998224  0.12269479 -0.33638471 -0.60240678]
hidden_outputs = [ 0.5061449   0.52045361  0.60108362  0.53063528  0.41668794  0.35379325]
final_inputs = [-0.12877889]
final_outputs = [-0.12877889]
error = [-0.04467887]
output_error_term = [-0.04467887]
hidden_error = [ 0.04525149  0.0225018   0.05122548  0.04163806 -0.11840935 -0.0915985 ]
hidden_error_term = [ 0.01131116  0.00561604  0.01228295  0.01037044 -0.02878047 -0.02094158]
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Progress: 3.4% ... Training loss: 0.274 ... Validation loss: 0.446hidden_inputs = [ 0.10158138 -0.06228402  0.59841956  0.34115812 -0.27293064 -0.31250895]
hidden_outputs = [ 0.52537353  0.48443403  0.64529464  0.58447182  0.43218777  0.42250245]
final_inputs = [-0.07256694]
final_outputs = [-0.07256694]
error = [-0.26076945]
output_error_term = [-0.26076945]
hidden_error = [ 0.26660402  0.13300759  0.30193615  0.24573858 -0.6900702  -0.53443953]
hidden_error_term = [ 0.06647936  0.03321967  0.06911     0.05968118 -0.16934426 -0.13040011]
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Progress: 3.4% ... Training loss: 0.274 ... Validation loss: 0.452hidden_inputs = [-0.1893379  -0.19056076 -0.67275828 -1.14278116 -0.97589186  0.68777829]
hidden_outputs = [ 0.45280643  0.45250345  0.33787949  0.2418101   0.27370769  0.66547251]
final_inputs = [ 0.78618043]
final_outputs = [ 0.78618043]
error = [-1.04233404]
output_error_term = [-1.04233404]
hidden_error = [ 1.0591255   0.52058193  1.20348491  0.98498255 -2.75242528 -2.1429258 ]
hidden_error_term = [ 0.26242246  0.12897109  0.26923996  0.18058471 -0.54715955 -0.47705567]
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Progress: 3.4% ... Training loss: 0.276 ... Validation loss: 0.446hidden_inputs = [ 0.87608417  0.97567576  0.54902036 -0.55387811 -3.08756319 -0.44404427]
hidden_outputs = [ 0.70601011  0.72624935  0.63390828  0.36496513  0.04362319  0.39077772]
final_inputs = [-1.25549111]
final_outputs = [-1.25549111]
error = [ 0.2219966]
output_error_term = [ 0.2219966]
hidden_error = [-0.2278099  -0.11140318 -0.25786254 -0.21155309  0.58737572  0.45569466]
hidden_error_term = [-0.04728419 -0.0221482  -0.05984179 -0.04903072  0.02450543  0.10848745]
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Progress: 3.4% ... Training loss: 0.293 ... Validation loss: 0.468hidden_inputs = [-0.28969663 -0.46129193 -1.37003394 -0.90269179 -0.75586233  0.67219249]
hidden_outputs = [ 0.42807814  0.38667939  0.20261436  0.28849765  0.31954527  0.66199392]
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error = [ 0.21977645]
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Progress: 3.4% ... Training loss: 0.275 ... Validation loss: 0.455hidden_inputs = [ 0.31817805  0.47144419  0.0705302  -0.60367192 -2.32654597 -0.19289625]
hidden_outputs = [ 0.57888017  0.61572552  0.51762524  0.35350407  0.08894817  0.45192491]
final_inputs = [-0.66035309]
final_outputs = [-0.66035309]
error = [-0.22980196]
output_error_term = [-0.22980196]
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Progress: 3.4% ... Training loss: 0.291 ... Validation loss: 0.457hidden_inputs = [-0.34490079 -0.57188534  0.08400803 -0.74111242 -0.54102976 -0.021698  ]
hidden_outputs = [ 0.41461951  0.36080191  0.52098967  0.32276093  0.36794807  0.49457571]
final_inputs = [ 0.40648158]
final_outputs = [ 0.40648158]
error = [ 0.41241074]
output_error_term = [ 0.41241074]
hidden_error = [-0.43487352 -0.2179596  -0.49029476 -0.40230713  1.08527924  0.83414082]
hidden_error_term = [-0.10554823 -0.05026669 -0.12235768 -0.08793883  0.25239502  0.20851066]
delta_weights_i_h = [[-0.72372001 -0.41806011 -0.87922405 -0.58662157  1.47104605  1.50343179]
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delta_weights_h_o = [[ 6.32277152]
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Progress: 3.4% ... Training loss: 0.276 ... Validation loss: 0.454hidden_inputs = [ 0.71679948 -0.64922496  0.00796864 -0.12413627 -0.57951158 -0.55906541]
hidden_outputs = [ 0.67190185  0.34316421  0.50199215  0.46900572  0.35904499  0.36376373]
final_inputs = [-0.19017189]
final_outputs = [-0.19017189]
error = [-0.68895705]
output_error_term = [-0.68895705]
hidden_error = [ 0.70606318  0.34266945  0.79787934  0.65348536 -1.82172907 -1.41276215]
hidden_error_term = [ 0.15565146  0.07723856  0.19946667  0.16274357 -0.41923758 -0.32696922]
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Progress: 3.4% ... Training loss: 0.274 ... Validation loss: 0.454hidden_inputs = [ 0.36301582  0.47330114  0.51672887  0.46336154 -1.2788309  -0.87484302]
hidden_outputs = [ 0.58977028  0.61616479  0.62638255  0.61381132  0.2177493   0.29424757]
final_inputs = [-1.0372304]
final_outputs = [-1.0372304]
error = [ 0.02027506]
output_error_term = [ 0.02027506]
hidden_error = [-0.02078604 -0.01010067 -0.02349633 -0.01918654  0.0537239   0.04162831]
hidden_error_term = [-0.005029   -0.00238887 -0.00549879 -0.00454811  0.00915104  0.00864478]
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Progress: 3.4% ... Training loss: 0.279 ... Validation loss: 0.451hidden_inputs = [-0.49396794  0.4861861   0.16993247 -0.27446761 -0.38011518 -0.25073981]
hidden_outputs = [ 0.37895927  0.61920756  0.54238118  0.43181063  0.40609912  0.43764142]
final_inputs = [ 0.20733327]
final_outputs = [ 0.20733327]
error = [-0.27052992]
output_error_term = [-0.27052992]
hidden_error = [ 0.28077446  0.13752011  0.3176686   0.25833113 -0.71453426 -0.5514133 ]
hidden_error_term = [ 0.06608003  0.03242581  0.07884657  0.0633816  -0.17233325 -0.1357091 ]
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delta_weights_h_o = [[ 8.02105645]
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self.weights_hidden_to_output = [[-1.00026975]
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Progress: 3.5% ... Training loss: 0.282 ... Validation loss: 0.472hidden_inputs = [ 0.37121192  0.19630461  0.27658293 -0.80093579 -0.98310855  0.02414164]
hidden_outputs = [ 0.59175179  0.54891916  0.56870829  0.30982538  0.27227542  0.50603512]
final_inputs = [-0.00709005]
final_outputs = [-0.00709005]
error = [-0.18841994]
output_error_term = [-0.18841994]
hidden_error = [ 0.18847077  0.08988811  0.21350113  0.17366194 -0.50335125 -0.39069992]
hidden_error_term = [ 0.04553107  0.02225692  0.05236738  0.03713476 -0.09973478 -0.09766075]
delta_weights_i_h = [[ 1.15300942  0.55748612  1.32203144  1.10108979 -2.27715418 -2.30271247]
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Progress: 3.5% ... Training loss: 0.273 ... Validation loss: 0.447hidden_inputs = [-0.47420504 -0.63152615  0.11441716  0.54143548 -1.28881607 -0.54219564]
hidden_outputs = [ 0.38362145  0.34716457  0.52857313  0.63214628  0.21605327  0.36767697]
final_inputs = [-0.44464669]
final_outputs = [-0.44464669]
error = [-0.55025643]
output_error_term = [-0.55025643]
hidden_error = [ 0.56304081  0.27498756  0.63720826  0.51604805 -1.46113494 -1.12636048]
hidden_error_term = [ 0.1331344   0.06232355  0.15878183  0.12000045 -0.24747864 -0.26186824]
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Progress: 3.5% ... Training loss: 0.275 ... Validation loss: 0.443hidden_inputs = [-0.21795974 -0.495652    0.16472308 -0.49204357  0.67775309 -0.23283223]
hidden_outputs = [ 0.44572476  0.37856301  0.54108791  0.37941227  0.66323703  0.44205348]
final_inputs = [ 1.05451015]
final_outputs = [ 1.05451015]
error = [-0.70974065]
output_error_term = [-0.70974065]
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hidden_error_term = [ 0.17854511  0.08304051  0.20325189  0.15610208 -0.42288512 -0.35869386]
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Progress: 3.5% ... Training loss: 0.279 ... Validation loss: 0.455hidden_inputs = [ 0.16598825  0.4332443   0.78317514  0.35326185 -1.62510928 -0.89727255]
hidden_outputs = [ 0.54140205  0.60664811  0.68636402  0.58740834  0.16450144  0.28961131]
final_inputs = [-1.22056808]
final_outputs = [-1.22056808]
error = [ 0.19258663]
output_error_term = [ 0.19258663]
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hidden_error_term = [-0.04933267 -0.02378457 -0.04865212 -0.04452208  0.06987419  0.07982894]
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Progress: 3.5% ... Training loss: 0.281 ... Validation loss: 0.466hidden_inputs = [-0.11074009  0.37956606  0.11046771  0.06125181 -0.21681808 -0.23478971]
hidden_outputs = [ 0.47234323  0.59376844  0.52758888  0.51530817  0.44600683  0.44157074]
final_inputs = [ 0.28040692]
final_outputs = [ 0.28040692]
error = [ 0.31245011]
output_error_term = [ 0.31245011]
hidden_error = [-0.30988568 -0.14831319 -0.35335599 -0.28670816  0.83446696  0.64325152]
hidden_error_term = [-0.07723439 -0.03577425 -0.08807004 -0.07160985  0.20618405  0.15861683]
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Progress: 3.5% ... Training loss: 0.280 ... Validation loss: 0.463hidden_inputs = [-0.02526781  0.11693663 -0.30285113  0.1638753  -1.29691079 -0.46825614]
hidden_outputs = [ 0.49368338  0.52920089  0.42486065  0.54087739  0.21468538  0.38502908]
final_inputs = [-0.36304466]
final_outputs = [-0.36304466]
error = [-0.48300594]
output_error_term = [-0.48300594]
hidden_error = [ 0.48136155  0.23306138  0.54944188  0.44506039 -1.29236721 -0.99299188]
hidden_error_term = [ 0.12032118  0.05806662  0.13425836  0.11052142 -0.21788739 -0.23512229]
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delta_weights_h_o = [[-1.96570585]
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self.weights_hidden_to_output = [[-1.00580975]
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Progress: 3.5% ... Training loss: 0.274 ... Validation loss: 0.458hidden_inputs = [ 0.12938615  0.42375115 -0.4026713  -1.03586108 -0.9971291   0.97733802]
hidden_outputs = [ 0.53230149  0.60438052  0.4006707   0.26194939  0.26950625  0.7265797 ]
final_inputs = [ 0.67091563]
final_outputs = [ 0.67091563]
error = [-0.45845947]
output_error_term = [-0.45845947]
hidden_error = [ 0.46112301  0.22577704  0.52431731  0.42718557 -1.22341382 -0.93831584]
hidden_error_term = [ 0.11479962  0.05398435  0.12590625  0.0825886  -0.2408567  -0.18640736]
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Progress: 3.5% ... Training loss: 0.273 ... Validation loss: 0.455hidden_inputs = [ 0.06776288 -0.76831635  0.16989444  0.57964782 -1.18294904 -0.53445294]
hidden_outputs = [ 0.51693424  0.31684343  0.54237174  0.64098636  0.23452236  0.36947891]
final_inputs = [-0.51812813]
final_outputs = [-0.51812813]
error = [-0.48780109]
output_error_term = [-0.48780109]
hidden_error = [ 0.49195328  0.24039251  0.5593576   0.45735487 -1.30266361 -0.99806791]
hidden_error_term = [ 0.12284724  0.05203384  0.13883515  0.1052478  -0.23385629 -0.23251414]
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delta_weights_h_o = [[-8.30065482]
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self.weights_hidden_to_output = [[-1.04742136]
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Progress: 3.5% ... Training loss: 0.297 ... Validation loss: 0.458hidden_inputs = [-0.44187693 -0.30789001  0.18355157 -0.6017866  -1.20547251  0.82064419]
hidden_outputs = [ 0.39129382  0.42362985  0.54575949  0.35393505  0.23050312  0.69437307]
final_inputs = [ 0.37958757]
final_outputs = [ 0.37958757]
error = [ 0.69841839]
output_error_term = [ 0.69841839]
hidden_error = [-0.73153834 -0.36634627 -0.82875971 -0.68286835  1.84442322  1.40472298]
hidden_error_term = [-0.17423997 -0.08944989 -0.20545456 -0.15614811  0.32714799  0.29810906]
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Progress: 3.5% ... Training loss: 0.275 ... Validation loss: 0.452hidden_inputs = [-0.8976414  -0.18684634 -0.69076036 -0.17037114  0.3352088   0.55979805]
hidden_outputs = [ 0.28953543  0.45342384  0.33386395  0.45750994  0.58302621  0.63640581]
final_inputs = [ 1.48985856]
final_outputs = [ 1.48985856]
error = [ 0.59703666]
output_error_term = [ 0.59703666]
hidden_error = [-0.61026168 -0.2995334  -0.69158595 -0.56745963  1.58289421  1.20937513]
hidden_error_term = [-0.12553367 -0.07423356 -0.15380789 -0.14084041  0.3848121   0.27984149]
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   -2.98709059e-01  -2.29259575e-01]
 [  1.11371075e-01  -1.50403522e-01   1.47191890e-01  -7.05842018e-03
   -1.69625521e-01  -1.98658498e-01]
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   -3.35671875e-01  -1.47419154e-01]
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   -2.43761172e-01   9.98253857e-02]
 [  5.47296646e-02  -1.30902419e-01   1.32166645e-01   9.64622696e-02
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Progress: 3.5% ... Training loss: 0.272 ... Validation loss: 0.450hidden_inputs = [-0.00217586 -0.27658651 -0.09042286  0.64663114 -1.54996727 -0.48357173]
hidden_outputs = [ 0.49945603  0.43129084  0.47740967  0.6562509   0.175091    0.38140907]
final_inputs = [-0.67227643]
final_outputs = [-0.67227643]
error = [ 0.07431335]
output_error_term = [ 0.07431335]
hidden_error = [-0.07615694 -0.03757069 -0.08623574 -0.07050224  0.19729222  0.1499038 ]
hidden_error_term = [-0.01903921 -0.0092153  -0.02151493 -0.01590429  0.02849573  0.03536773]
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delta_weights_h_o = [[ 2.91854868]
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self.weights_hidden_to_output = [[-1.0111276 ]
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   -1.75089581e-01  -2.01822865e-01]
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Progress: 3.6% ... Training loss: 0.273 ... Validation loss: 0.450hidden_inputs = [ 0.95154552 -0.06561727  0.19091894 -0.33229283 -0.03486362 -0.55413709]
hidden_outputs = [ 0.72142589  0.48360157  0.54758528  0.41768285  0.49128498  0.36490511]
final_inputs = [ 0.06462258]
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Progress: 3.6% ... Training loss: 0.291 ... Validation loss: 0.476hidden_inputs = [ 0.08338921 -0.31005314  0.33464917  0.1836776  -0.73145047 -0.08262238]
hidden_outputs = [ 0.52083523  0.42310177  0.58289016  0.54579073  0.32487651  0.47935615]
final_inputs = [-0.00639733]
final_outputs = [-0.00639733]
error = [-0.37104351]
output_error_term = [-0.37104351]
hidden_error = [ 0.36695054  0.17394273  0.41640649  0.33903303 -0.99709529 -0.7638789 ]
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Progress: 3.6% ... Training loss: 0.272 ... Validation loss: 0.451hidden_inputs = [-0.16021501 -0.25405652 -0.68622883 -0.581472   -2.07142564  0.02583437]
hidden_outputs = [ 0.46003171  0.43682531  0.33487251  0.35859396  0.11190528  0.50645823]
final_inputs = [-0.09548039]
final_outputs = [-0.09548039]
error = [ 0.31896266]
output_error_term = [ 0.31896266]
hidden_error = [-0.32670877 -0.15966743 -0.37035531 -0.30251567  0.84984029  0.64563859]
hidden_error_term = [-0.08115529 -0.03927962 -0.08249032 -0.06957991  0.08445924  0.16138272]
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Progress: 3.6% ... Training loss: 0.279 ... Validation loss: 0.455hidden_inputs = [ 0.44639646 -0.12242179  0.14636267 -0.4356558  -1.99198268 -0.66795273]
hidden_outputs = [ 0.60978212  0.46943272  0.53652549  0.39277659  0.12004726  0.33895541]
final_inputs = [-0.87235653]
final_outputs = [-0.87235653]
error = [ 0.04835816]
output_error_term = [ 0.04835816]
hidden_error = [-0.05011491 -0.024624   -0.05688249 -0.04635888  0.1287777   0.09795127]
hidden_error_term = [-0.01192474 -0.00613299 -0.01414474 -0.01105674  0.01360355  0.02194742]
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Progress: 3.6% ... Training loss: 0.275 ... Validation loss: 0.454hidden_inputs = [ 0.60167231  0.65912633  0.38441829 -0.21441896 -2.96693551 -0.70837935]
hidden_outputs = [ 0.64603881  0.6590641   0.5949383   0.4465997   0.04894217  0.32995704]
final_inputs = [-1.31646753]
final_outputs = [-1.31646753]
error = [ 0.3105383]
output_error_term = [ 0.3105383]
hidden_error = [-0.31921738 -0.155577   -0.36257334 -0.29568899  0.82652678  0.62814179]
hidden_error_term = [-0.07299629 -0.03495794 -0.08737536 -0.07307906  0.0384722   0.13887297]
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Progress: 3.6% ... Training loss: 0.294 ... Validation loss: 0.471hidden_inputs = [-0.13050446 -0.3938419  -0.02817001 -0.18774518 -0.78508249 -0.25956784]
hidden_outputs = [ 0.46742011  0.40279279  0.49295796  0.45320109  0.31322553  0.43546994]
final_inputs = [ 0.121564]
final_outputs = [ 0.121564]
error = [-0.58721374]
output_error_term = [-0.58721374]
hidden_error = [ 0.58155543  0.27722161  0.66532734  0.53706521 -1.58943638 -1.21340755]
hidden_error_term = [ 0.14477156  0.06668587  0.16629884  0.13309005 -0.34191208 -0.2982991 ]
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Progress: 3.6% ... Training loss: 0.281 ... Validation loss: 0.456hidden_inputs = [ 0.33547151  0.01752816 -0.16308492 -1.44151358 -2.15652529 -0.13491477]
hidden_outputs = [ 0.58309008  0.50438193  0.4593189   0.19131107  0.10372303  0.46632237]
final_inputs = [-0.3719484]
final_outputs = [-0.3719484]
error = [ 0.1654123]
output_error_term = [ 0.1654123]
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Progress: 3.6% ... Training loss: 0.274 ... Validation loss: 0.449hidden_inputs = [-0.15719776  0.02987569 -0.53028668 -0.60379595 -0.57630227  0.62960607]
hidden_outputs = [ 0.46078129  0.50746837  0.37045003  0.35347572  0.35978388  0.65240013]
final_inputs = [ 0.78837569]
final_outputs = [ 0.78837569]
error = [-0.42706702]
output_error_term = [-0.42706702]
hidden_error = [ 0.43815066  0.21406944  0.49940519  0.40611599 -1.14013411 -0.86690553]
hidden_error_term = [ 0.10886374  0.05350542  0.11646968  0.09280995 -0.26261785 -0.19659181]
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Progress: 3.6% ... Training loss: 0.274 ... Validation loss: 0.447hidden_inputs = [ 0.350328    0.16637762  0.66167099 -0.17263074  0.58176754 -0.10042082]
hidden_outputs = [ 0.58669712  0.54149872  0.65963565  0.45694918  0.64147402  0.47491587]
final_inputs = [ 0.6604507]
final_outputs = [ 0.6604507]
error = [ 0.52230333]
output_error_term = [ 0.52230333]
hidden_error = [-0.52752537 -0.25524904 -0.59954925 -0.4868978   1.40724799  1.06951327]
hidden_error_term = [-0.12791626 -0.06337268 -0.13460867 -0.12082205  0.32364607  0.26670537]
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self.weights_hidden_to_output = [[-1.03394124]
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Progress: 3.6% ... Training loss: 0.271 ... Validation loss: 0.442hidden_inputs = [ 0.57519483 -0.43300224  0.2125393   0.31601689  0.14393687 -0.21050923]
hidden_outputs = [ 0.63996099  0.39340965  0.5529357   0.57835323  0.53592222  0.44756618]
final_inputs = [ 0.28543572]
final_outputs = [ 0.28543572]
error = [-0.53607627]
output_error_term = [-0.53607627]
hidden_error = [ 0.55427136  0.2751781   0.62581914  0.50734749 -1.43784128 -1.08336558]
hidden_error_term = [ 0.12771017  0.06566809  0.15470112  0.12372215 -0.35760492 -0.26786289]
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delta_weights_h_o = [[ 4.15597358]
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self.weights_hidden_to_output = [[-1.01446011]
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Progress: 3.7% ... Training loss: 0.273 ... Validation loss: 0.450hidden_inputs = [ 0.10792069  0.1264552   0.7821035  -0.50544652 -2.23906272 -0.66531436]
hidden_outputs = [ 0.52695402  0.53157174  0.68613329  0.37626157  0.09629708  0.33954683]
final_inputs = [-0.98407183]
final_outputs = [-0.98407183]
error = [ 0.34751735]
output_error_term = [ 0.34751735]
hidden_error = [-0.35254249 -0.17187813 -0.39916047 -0.32473533  0.93644271  0.70989684]
hidden_error_term = [-0.08787949 -0.04279821 -0.08596096 -0.07621175  0.08149294  0.15919776]
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Progress: 3.7% ... Training loss: 0.274 ... Validation loss: 0.447hidden_inputs = [ 0.51015688  0.41981019 -0.08444342 -0.58800974 -1.69672738 -0.18297201]
hidden_outputs = [ 0.62484325  0.60343783  0.47890168  0.35709164  0.15489317  0.45438419]
final_inputs = [-0.5147899]
final_outputs = [-0.5147899]
error = [-0.30369543]
output_error_term = [-0.30369543]
hidden_error = [ 0.31368613  0.15376667  0.35378352  0.29010587 -0.81430552 -0.6147782 ]
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Progress: 3.7% ... Training loss: 0.280 ... Validation loss: 0.463hidden_inputs = [-0.35105764  0.36441766 -0.27576227 -0.228958   -1.05223345 -0.20847069]
hidden_outputs = [ 0.41312597  0.5901094   0.43149302  0.44300925  0.25879645  0.44807026]
final_inputs = [-0.05899421]
final_outputs = [-0.05899421]
error = [-0.47832525]
output_error_term = [-0.47832525]
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hidden_error_term = [ 0.11976789  0.05931869  0.13687737  0.11234365 -0.24526753 -0.23850931]
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delta_weights_h_o = [[ 4.87047709]
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   -1.78736400e-01  -1.96864271e-01]
 [ -2.31269599e-01  -4.60479760e-02   5.95128940e-03   1.60620441e-01
   -3.17959553e-01  -1.24462500e-01]
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   -2.38374157e-01   1.06533237e-01]
 [  7.96656888e-02  -1.19117545e-01   1.61918260e-01   1.17654903e-01
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Progress: 3.7% ... Training loss: 0.280 ... Validation loss: 0.457hidden_inputs = [-0.12072162  0.25402833  0.83949835  0.17056348 -1.95385795 -0.74725683]
hidden_outputs = [ 0.4698562   0.56316776  0.69835955  0.54253779  0.1241333   0.32141932]
final_inputs = [-1.05844646]
final_outputs = [-1.05844646]
error = [ 0.05803029]
output_error_term = [ 0.05803029]
hidden_error = [-0.05860517 -0.02853151 -0.06624374 -0.053894    0.15714104  0.11877667]
hidden_error_term = [-0.01459804 -0.00701903 -0.01395447 -0.01337598  0.01708504  0.02590625]
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delta_weights_h_o = [[-5.88957332]
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self.weights_hidden_to_output = [[-1.03751397]
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self.weights_input_to_hidden = [[ -1.81447304e-01  -2.94372520e-01  -3.34130579e-01  -4.65705951e-01
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   -3.03608590e-01  -1.30680355e-01]
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   -1.87080065e-01  -6.58886142e-02]
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   -1.89416089e-01  -2.05200215e-01]
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   -3.21484498e-01  -1.28230267e-01]
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   -2.38599764e-01   1.06118934e-01]
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Progress: 3.7% ... Training loss: 0.275 ... Validation loss: 0.451hidden_inputs = [ 0.22057083 -0.19342427 -0.14394816 -0.30358489 -1.36821284 -0.75511684]
hidden_outputs = [ 0.55492023  0.45179413  0.46407497  0.42468136  0.20290874  0.31970739]
final_inputs = [-0.56802082]
final_outputs = [-0.56802082]
error = [-0.43239535]
output_error_term = [-0.43239535]
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Progress: 3.7% ... Training loss: 0.272 ... Validation loss: 0.449hidden_inputs = [ 0.43366955  0.23899403 -0.14189604 -0.71339935 -2.55356105 -0.30722724]
hidden_outputs = [ 0.60674958  0.55946573  0.46458539  0.32884814  0.07218761  0.42379168]
final_inputs = [-0.66916945]
final_outputs = [-0.66916945]
error = [ 0.12082387]
output_error_term = [ 0.12082387]
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   -1.93127190e-01  -2.03461260e-01]
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Progress: 3.7% ... Training loss: 0.271 ... Validation loss: 0.441hidden_inputs = [ 0.23118171  0.01954928  1.03223396  0.70418982 -1.5446639  -0.55709782]
hidden_outputs = [ 0.55753939  0.50488716  0.73734877  0.66911605  0.1758583   0.36421923]
final_inputs = [-1.10445641]
final_outputs = [-1.10445641]
error = [ 0.09301413]
output_error_term = [ 0.09301413]
hidden_error = [-0.09599    -0.04731873 -0.10801795 -0.08772948  0.25122596  0.18902547]
hidden_error_term = [-0.0236797  -0.01182855 -0.02091936 -0.01942329  0.03641072  0.04377141]
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Progress: 3.7% ... Training loss: 0.274 ... Validation loss: 0.444hidden_inputs = [-0.43450931 -0.31577544 -0.12658113  0.71998006 -0.46867569 -0.23210752]
hidden_outputs = [ 0.39305007  0.42170565  0.4683969   0.67260263  0.38492974  0.44223223]
final_inputs = [ 0.17652674]
final_outputs = [ 0.17652674]
error = [-0.46024563]
output_error_term = [-0.46024563]
hidden_error = [ 0.46887815  0.22789184  0.52875115  0.42703988 -1.2474173  -0.94151223]
hidden_error_term = [ 0.11185637  0.05557598  0.13165969  0.09403774 -0.29533707 -0.23223612]
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Progress: 3.7% ... Training loss: 0.271 ... Validation loss: 0.446hidden_inputs = [ 0.01031832 -0.31371803 -0.15122737  0.08527359 -0.80494113 -0.37049986]
hidden_outputs = [ 0.50257956  0.42220747  0.46226505  0.52130549  0.30896956  0.40842024]
final_inputs = [-0.10862998]
final_outputs = [-0.10862998]
error = [-0.31842836]
output_error_term = [-0.31842836]
hidden_error = [ 0.32987404  0.16262978  0.37223437  0.30142379 -0.85831006 -0.64608386]
hidden_error_term = [ 0.08246632  0.03967326  0.09252856  0.07521912 -0.18325552 -0.15610235]
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Progress: 3.8% ... Training loss: 0.273 ... Validation loss: 0.448hidden_inputs = [ 0.41936339 -0.94096722  0.00688688  0.11046525 -0.19746168  0.05868436]
hidden_outputs = [ 0.6033309   0.28070501  0.50172171  0.52758826  0.45079436  0.51466688]
final_inputs = [ 0.459545]
final_outputs = [ 0.459545]
error = [ 0.91616598]
output_error_term = [ 0.91616598]
hidden_error = [-0.93316083 -0.45224652 -1.05390676 -0.84983205  2.48642813  1.87933928]
hidden_error_term = [-0.22332659 -0.09131296 -0.26347357 -0.2118112   0.61558691  0.46943054]
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Progress: 3.8% ... Training loss: 0.288 ... Validation loss: 0.439hidden_inputs = [-0.36134708  0.4216303   0.34749182 -0.66634224 -0.38211397  0.22400825]
hidden_outputs = [ 0.41063352  0.6038733   0.58600922  0.33931636  0.40561714  0.55576905]
final_inputs = [ 0.56710281]
final_outputs = [ 0.56710281]
error = [-0.76812586]
output_error_term = [-0.76812586]
hidden_error = [ 0.77756497  0.37499396  0.87918016  0.70700683 -2.10424556 -1.58867791]
hidden_error_term = [ 0.18818132  0.08970243  0.21329123  0.15849733 -0.50731651 -0.39222839]
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Progress: 3.8% ... Training loss: 0.275 ... Validation loss: 0.447hidden_inputs = [ 1.30388336  0.40557136  0.26138093 -0.94862512 -3.32166588 -0.68704022]
hidden_outputs = [ 0.78648782  0.6000255   0.56497573  0.2791614   0.03483536  0.33469181]
final_inputs = [-1.24292826]
final_outputs = [-1.24292826]
error = [ 0.20943375]
output_error_term = [ 0.20943375]
hidden_error = [-0.21553939 -0.10521757 -0.24348459 -0.19500914  0.57142623  0.43155304]
hidden_error_term = [-0.03619439 -0.02525168 -0.05984319 -0.03924175  0.01921241  0.0960953 ]
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Progress: 3.8% ... Training loss: 0.275 ... Validation loss: 0.444hidden_inputs = [ 0.30153942  0.44682709  0.65115194  0.50534766 -1.1375525  -0.386974  ]
hidden_outputs = [ 0.5748188   0.60988458  0.65727     0.62371522  0.24277001  0.40444596]
final_inputs = [-0.8131208]
final_outputs = [-0.8131208]
error = [ 0.24272299]
output_error_term = [ 0.24272299]
hidden_error = [-0.25576197 -0.12711109 -0.28771797 -0.23061537  0.65938183  0.49461575]
hidden_error_term = [-0.06250877 -0.03024295 -0.06481312 -0.05412417  0.12121596  0.11913781]
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Progress: 3.8% ... Training loss: 0.272 ... Validation loss: 0.437hidden_inputs = [-0.14291422 -0.67093494 -0.05460354  0.05616906  1.30216378  0.17764478]
hidden_outputs = [ 0.46433213  0.33828752  0.48635251  0.51403857  0.78619892  0.54429477]
final_inputs = [ 1.55526566]
final_outputs = [ 1.55526566]
error = [-0.11891106]
output_error_term = [-0.11891106]
hidden_error = [ 0.12384171  0.06072082  0.13951755  0.11193172 -0.32509833 -0.2439543 ]
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Progress: 3.8% ... Training loss: 0.270 ... Validation loss: 0.437hidden_inputs = [ 0.59168894 -0.16917465  0.2979498  -0.46736976 -0.54231299 -0.2749759 ]
hidden_outputs = [ 0.64375257  0.45780692  0.57394125  0.38523898  0.36764969  0.43168593]
final_inputs = [-0.01854688]
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output_error_term = [ 0.17035942]
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Progress: 3.8% ... Training loss: 0.274 ... Validation loss: 0.427hidden_inputs = [ 0.43084582  0.12530278 -0.14558568 -0.51702061 -2.58917268 -0.04410677]
hidden_outputs = [ 0.60607562  0.53128477  0.46366773  0.37354918  0.06983851  0.48897509]
final_inputs = [-0.56504477]
final_outputs = [-0.56504477]
error = [ 0.36953478]
output_error_term = [ 0.36953478]
hidden_error = [-0.37853065 -0.18395805 -0.4277081  -0.34166567  1.0171031   0.76334977]
hidden_error_term = [-0.09037342 -0.04580947 -0.10636244 -0.07995325  0.06607213  0.19074466]
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Progress: 3.8% ... Training loss: 0.282 ... Validation loss: 0.433hidden_inputs = [-0.02505067 -0.11287774  0.00986372  0.41274194  0.06411464 -0.44837173]
hidden_outputs = [ 0.49373766  0.47181049  0.50246591  0.60174516  0.51602317  0.38974797]
final_inputs = [ 0.36445625]
final_outputs = [ 0.36445625]
error = [-0.46624428]
output_error_term = [-0.46624428]
hidden_error = [ 0.4775456   0.23202465  0.5369831   0.4301019  -1.29086072 -0.9690697 ]
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Progress: 3.8% ... Training loss: 0.275 ... Validation loss: 0.439hidden_inputs = [ 0.03717429 -0.45928507 -0.01376514  0.23545852  0.72105952 -0.26858367]
hidden_outputs = [ 0.5092925   0.38715544  0.49655877  0.55859417  0.67284029  0.43325484]
final_inputs = [ 0.88317726]
final_outputs = [ 0.88317726]
error = [-0.40058135]
output_error_term = [-0.40058135]
hidden_error = [ 0.42068863  0.20629312  0.47247069  0.37946946 -1.09621156 -0.82378537]
hidden_error_term = [ 0.10513583  0.04894636  0.11811208  0.09356454 -0.24130492 -0.20227645]
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delta_weights_h_o = [[ 3.81223927]
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self.weights_hidden_to_output = [[-1.03232537]
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Progress: 3.8% ... Training loss: 0.270 ... Validation loss: 0.438hidden_inputs = [ 0.14522474  0.02874622 -0.33368193 -0.81952305 -2.50654449 -0.24571336]
hidden_outputs = [ 0.53624251  0.50718606  0.41734502  0.30586491  0.07540066  0.43887887]
final_inputs = [-0.45649785]
final_outputs = [-0.45649785]
error = [-0.26826552]
output_error_term = [-0.26826552]
hidden_error = [ 0.2769373   0.13405305  0.31066678  0.24894565 -0.73868504 -0.55626829]
hidden_error_term = [ 0.06887056  0.03350634  0.07554427  0.05285404 -0.05149772 -0.13698897]
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Progress: 3.9% ... Training loss: 0.269 ... Validation loss: 0.429hidden_inputs = [ 0.36864602 -0.19549123  0.38362657  0.33482185 -0.02088432 -0.20005201]
hidden_outputs = [ 0.59113177  0.45128225  0.59474749  0.58293214  0.49477911  0.45015313]
final_inputs = [ 0.20252183]
final_outputs = [ 0.20252183]
error = [ 0.05955183]
output_error_term = [ 0.05955183]
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 [ 0.06815927 -0.12547436  0.14872398  0.10595128 -0.25570202  0.04171876]]
Progress: 3.9% ... Training loss: 0.277 ... Validation loss: 0.442hidden_inputs = [  5.31221787e-05   4.31629062e-01  -2.32375137e-01  -2.17397600e-01
  -1.46055325e+00  -4.40501247e-01]
hidden_outputs = [ 0.50001328  0.60626261  0.44216623  0.44586365  0.18838272  0.39162154]
final_inputs = [-0.48673861]
final_outputs = [-0.48673861]
error = [-0.07814613]
output_error_term = [-0.07814613]
hidden_error = [ 0.08263309  0.04121142  0.09256135  0.07443221 -0.21330405 -0.15881958]
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delta_weights_h_o = [[ 2.64457428]
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self.weights_hidden_to_output = [[-1.0450211 ]
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Progress: 3.9% ... Training loss: 0.283 ... Validation loss: 0.453hidden_inputs = [-0.31081912  0.12973111 -0.37165075 -0.11494932 -0.59218331 -0.29062583]
hidden_outputs = [ 0.42291481  0.53238737  0.4081422   0.47129427  0.35613406  0.42785066]
final_inputs = [ 0.1888089]
final_outputs = [ 0.1888089]
error = [ 0.0567256]
output_error_term = [ 0.0567256]
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hidden_error_term = [-0.01446762 -0.00733084 -0.0161399  -0.01342691  0.03535949  0.0281531 ]
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Progress: 3.9% ... Training loss: 0.269 ... Validation loss: 0.435hidden_inputs = [ 0.10665105 -0.37702261 -0.17303514 -0.22842977 -1.06113116 -0.12933014]
hidden_outputs = [ 0.52663752  0.40684521  0.45684883  0.44313959  0.25709335  0.46771246]
final_inputs = [-0.02322588]
final_outputs = [-0.02322588]
error = [-0.00137937]
output_error_term = [-0.00137937]
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hidden_error_term = [ 0.00035271  0.00016564  0.00039586  0.00031853 -0.00072226 -0.00070313]
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Progress: 3.9% ... Training loss: 0.270 ... Validation loss: 0.436hidden_inputs = [-0.20641264 -0.01779012  0.26720552  0.26330663  0.01690575 -0.40633812]
hidden_outputs = [ 0.44857928  0.49555259  0.56640673  0.56544896  0.50422634  0.3997905 ]
final_inputs = [ 0.28593732]
final_outputs = [ 0.28593732]
error = [ 0.55500722]
output_error_term = [ 0.55500722]
hidden_error = [-0.57479726 -0.28130607 -0.64511279 -0.524294    1.51839114  1.13105814]
hidden_error_term = [-0.1421795  -0.07032095 -0.15843334 -0.12882765  0.37957066  0.27140651]
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Progress: 3.9% ... Training loss: 0.273 ... Validation loss: 0.434hidden_inputs = [ 0.28481485 -0.2660752  -0.02368233 -0.81364407 -1.4091021  -0.2405963 ]
hidden_outputs = [ 0.57072625  0.43387088  0.4940797   0.30711451  0.19637572  0.44013941]
final_inputs = [-0.21945421]
final_outputs = [-0.21945421]
error = [-0.38953498]
output_error_term = [-0.38953498]
hidden_error = [ 0.40015049  0.19180819  0.44968651  0.36662127 -1.06927796 -0.79726273]
hidden_error_term = [ 0.09803599  0.04711326  0.11240587  0.07801524 -0.16874521 -0.19645886]
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Progress: 3.9% ... Training loss: 0.269 ... Validation loss: 0.440hidden_inputs = [ 0.1888835   0.15598048  0.56338547  0.21423986 -0.58995104 -0.04990872]
hidden_outputs = [ 0.54708098  0.53891625  0.63723551  0.55335604  0.35664609  0.48752541]
final_inputs = [-0.09310094]
final_outputs = [-0.09310094]
error = [-0.09138294]
output_error_term = [-0.09138294]
hidden_error = [ 0.09300836  0.04458444  0.10490438  0.08561647 -0.25073039 -0.1870789 ]
hidden_error_term = [ 0.02304593  0.01107859  0.02425037  0.02116038 -0.05753    -0.04674061]
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Progress: 3.9% ... Training loss: 0.277 ... Validation loss: 0.442hidden_inputs = [-0.57324036 -0.17831688 -0.72959806 -0.96891792 -1.72228896  0.61290213]
hidden_outputs = [ 0.36048946  0.45553853  0.32528294  0.27509624  0.15157657  0.64860253]
final_inputs = [ 0.47542963]
final_outputs = [ 0.47542963]
error = [ 0.81207246]
output_error_term = [ 0.81207246]
hidden_error = [-0.84406615 -0.41087184 -0.94941787 -0.77616382  2.21323531  1.64107096]
hidden_error_term = [-0.19458832 -0.10190574 -0.20837249 -0.15478127  0.28462452  0.37402844]
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Progress: 3.9% ... Training loss: 0.277 ... Validation loss: 0.443hidden_inputs = [ 0.36524933  0.23830172 -0.66175575 -0.48795349 -2.92697274 -0.31717304]
hidden_outputs = [ 0.59031055  0.55929509  0.34034532  0.38037579  0.0508362   0.42136485]
final_inputs = [-0.59691307]
final_outputs = [-0.59691307]
error = [ 0.0099761]
output_error_term = [ 0.0099761]
hidden_error = [-0.01001906 -0.00476144 -0.01132007 -0.00926496  0.0274359   0.02042103]
hidden_error_term = [-0.00242305 -0.00117362 -0.00254147 -0.00218366  0.00132383  0.00497898]
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Progress: 3.9% ... Training loss: 0.271 ... Validation loss: 0.448hidden_inputs = [-0.67265822 -0.47793955 -0.07794929 -0.36070791 -0.28848932 -0.02329721]
hidden_outputs = [ 0.33790188  0.38273879  0.48052254  0.41078821  0.42837375  0.49417596]
final_inputs = [ 0.70412663]
final_outputs = [ 0.70412663]
error = [ 0.56683629]
output_error_term = [ 0.56683629]
hidden_error = [-0.57830341 -0.27769953 -0.65188557 -0.53379853  1.54664291  1.15506094]
hidden_error_term = [-0.12938047 -0.06560646 -0.16272409 -0.12920127  0.37872596  0.28872605]
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Progress: 4.0% ... Training loss: 0.279 ... Validation loss: 0.450hidden_inputs = [ 0.4975504   0.30881227  0.2978082   0.35157055 -1.73386324 -0.4527571 ]
hidden_outputs = [ 0.62188349  0.57659532  0.57390663  0.58699838  0.1500941   0.38870544]
final_inputs = [-0.95544612]
final_outputs = [-0.95544612]
error = [ 0.00464746]
output_error_term = [ 0.00464746]
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hidden_error_term = [-0.00112557 -0.00056395 -0.00131632 -0.00107591  0.00161298  0.00224029]
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Progress: 4.0% ... Training loss: 0.276 ... Validation loss: 0.446hidden_inputs = [-0.35582607  0.16937545  0.54533975  0.44158769 -2.23247054 -0.61475614]
hidden_outputs = [ 0.41197033  0.54224292  0.6330537   0.60863728  0.09687228  0.35097502]
final_inputs = [-1.03441761]
final_outputs = [-1.03441761]
error = [ 0.01746227]
output_error_term = [ 0.01746227]
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delta_weights_h_o = [[ 4.81145183]
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Progress: 4.0% ... Training loss: 0.270 ... Validation loss: 0.446hidden_inputs = [ 0.46950207 -0.34800874  0.18119337 -0.70494555 -1.90815273  0.11581884]
hidden_outputs = [ 0.6152659   0.41386538  0.54517481  0.33071665  0.12918853  0.52892239]
final_inputs = [-0.31174634]
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error = [-0.13736423]
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Progress: 4.0% ... Training loss: 0.270 ... Validation loss: 0.445hidden_inputs = [-0.35798337 -0.54111494  0.18211152  0.07952537  0.59597706  0.04531635]
hidden_outputs = [ 0.41144782  0.36792826  0.54540247  0.51987087  0.64473538  0.51132715]
final_inputs = [ 1.11572963]
final_outputs = [ 1.11572963]
error = [-0.58902927]
output_error_term = [-0.58902927]
hidden_error = [ 0.59359249  0.28441656  0.67218795  0.55016978 -1.61641852 -1.20576943]
hidden_error_term = [ 0.14374347  0.06614308  0.16666135  0.13732521 -0.37024336 -0.30128765]
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self.weights_hidden_to_output = [[-1.01556921]
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Progress: 4.0% ... Training loss: 0.274 ... Validation loss: 0.455hidden_inputs = [-0.30650975 -0.05055774  0.48675834 -0.42515344 -1.58873312 -0.46184691]
hidden_outputs = [ 0.4239669   0.48736326  0.61934248  0.39528424  0.16956221  0.38654778]
final_inputs = [-0.49126353]
final_outputs = [-0.49126353]
error = [-0.25555206]
output_error_term = [-0.25555206]
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Progress: 4.0% ... Training loss: 0.274 ... Validation loss: 0.450hidden_inputs = [-0.11290118 -0.46125684  0.21312257 -0.90001677 -0.58259819  0.48166472]
hidden_outputs = [ 0.47180465  0.38668771  0.55307988  0.28904705  0.35833497  0.6181409 ]
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output_error_term = [ 1.10985494]
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Progress: 4.0% ... Training loss: 0.272 ... Validation loss: 0.449hidden_inputs = [ 0.49698446 -0.3100546   0.32798007  1.08004077 -1.71378905 -0.51653298]
hidden_outputs = [ 0.62175041  0.42310141  0.58126782  0.7465017   0.1526729   0.3736633 ]
final_inputs = [-1.05042452]
final_outputs = [-1.05042452]
error = [ 0.03898223]
output_error_term = [ 0.03898223]
hidden_error = [-0.04005062 -0.01937138 -0.04517472 -0.03708397  0.10714885  0.07957107]
hidden_error_term = [-0.00941898 -0.00472829 -0.01099533 -0.00701766  0.01386119  0.01862274]
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self.weights_hidden_to_output = [[-1.03852161]
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Progress: 4.0% ... Training loss: 0.273 ... Validation loss: 0.441hidden_inputs = [ 0.16678574  0.43095572  0.26045582  0.06557393 -4.1738399  -0.59405379]
hidden_outputs = [ 0.54160005  0.60610186  0.56474834  0.51638761  0.01515969  0.35570527]
final_inputs = [-1.26870939]
final_outputs = [-1.26870939]
error = [ 0.23521488]
output_error_term = [ 0.23521488]
hidden_error = [-0.24427573 -0.12005187 -0.27534106 -0.22580647  0.64519345  0.47501469]
hidden_error_term = [-0.0606462  -0.02866147 -0.06768094 -0.05639098  0.00963265  0.10886341]
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Progress: 4.0% ... Training loss: 0.272 ... Validation loss: 0.435hidden_inputs = [ 0.31860094  0.29081155  0.46177179 -0.22228828 -0.46306406 -0.06339948]
hidden_outputs = [ 0.57898325  0.5721948   0.61343441  0.44465563  0.38625919  0.48415544]
final_inputs = [ 0.04254647]
final_outputs = [ 0.04254647]
error = [ 0.84250253]
output_error_term = [ 0.84250253]
hidden_error = [-0.86065848 -0.41721144 -0.96816849 -0.79496723  2.31687275  1.70474114]
hidden_error_term = [-0.20979553 -0.10212832 -0.22958435 -0.19630682  0.54924487  0.42575731]
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Progress: 4.0% ... Training loss: 0.281 ... Validation loss: 0.450hidden_inputs = [ 0.32142325 -0.32608245  0.88642246 -0.37154273 -1.70006136 -0.81262809]
hidden_outputs = [ 0.57967107  0.41919413  0.70815134  0.4081683   0.15445725  0.30733075]
final_inputs = [-1.00921126]
final_outputs = [-1.00921126]
error = [ 0.04738648]
output_error_term = [ 0.04738648]
hidden_error = [-0.04946422 -0.02447977 -0.05573012 -0.04561933  0.12949795  0.09499734]
hidden_error_term = [-0.01205208 -0.0059601  -0.01151791 -0.01102012  0.01691246  0.0202229 ]
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Progress: 4.0% ... Training loss: 0.270 ... Validation loss: 0.445hidden_inputs = [ 0.00500451 -0.38675102  0.45233352 -0.34777769 -0.91818055  0.00463834]
hidden_outputs = [ 0.50125113  0.40449967  0.61119391  0.41392143  0.28532876  0.50115958]
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final_outputs = [-0.00666679]
error = [ 0.07578349]
output_error_term = [ 0.07578349]
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Progress: 4.1% ... Training loss: 0.277 ... Validation loss: 0.439hidden_inputs = [-0.28056568 -0.63835729 -0.39824058  0.28293816  1.07103069  0.77354431]
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error = [-0.83372547]
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Progress: 4.1% ... Training loss: 0.280 ... Validation loss: 0.456hidden_inputs = [-0.12200026 -0.30662821 -0.3681663   0.26783032 -0.19069397  0.25043633]
hidden_outputs = [ 0.46953771  0.42393797  0.40898418  0.56656017  0.45247045  0.56228389]
final_inputs = [ 0.65517058]
final_outputs = [ 0.65517058]
error = [ 0.51104428]
output_error_term = [ 0.51104428]
hidden_error = [-0.52869478 -0.26156539 -0.59568347 -0.48383754  1.39999782  1.02837973]
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Progress: 4.1% ... Training loss: 0.291 ... Validation loss: 0.449hidden_inputs = [ 0.3836264  -0.18291371  0.51935231 -0.42965863 -0.61965698 -0.00779733]
hidden_outputs = [ 0.59474745  0.45439864  0.6269963   0.39420785  0.34985947  0.49805068]
final_inputs = [ 0.15308219]
final_outputs = [ 0.15308219]
error = [ 0.13655675]
output_error_term = [ 0.13655675]
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 [ 0.07578256  0.17301169  0.0928624   0.20093535 -0.25992343 -0.09817665]
 [-0.0333891   0.00519861 -0.15147697  0.02256212 -0.28514037 -0.2154682 ]
 [ 0.10980854 -0.15288025  0.13945067 -0.01205444 -0.20725376 -0.18936486]
 [-0.21582477 -0.04178219  0.01796007  0.16715392 -0.3557753  -0.14543042]
 [ 0.2024186   0.13387184  0.26808978 -0.03049561 -0.24153605  0.10633167]
 [ 0.07925212 -0.12115086  0.1630272   0.11259485 -0.27847601  0.03102187]]
Progress: 4.1% ... Training loss: 0.269 ... Validation loss: 0.438hidden_inputs = [ 0.49903271  0.12067841 -0.32767237 -1.02185697 -2.68621477 -0.3633445 ]
hidden_outputs = [ 0.62223199  0.53013304  0.41880708  0.26466584  0.06379171  0.4101502 ]
final_inputs = [-0.59683891]
final_outputs = [-0.59683891]
error = [-0.06728084]
output_error_term = [-0.06728084]
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hidden_error_term = [ 0.01595188  0.00819985  0.01867417  0.01210969 -0.0111188  -0.03317602]
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delta_weights_h_o = [[-4.25654869]
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self.weights_hidden_to_output = [[-1.02860816]
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Progress: 4.1% ... Training loss: 0.280 ... Validation loss: 0.457hidden_inputs = [ 0.15693104 -0.26426023  0.29474948 -0.28290549 -0.15549901 -0.00754176]
hidden_outputs = [ 0.53915244  0.43431674  0.57315849  0.4297416   0.46120339  0.49811457]
final_inputs = [ 0.4246271]
final_outputs = [ 0.4246271]
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output_error_term = [ 0.27297799]
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Progress: 4.1% ... Training loss: 0.272 ... Validation loss: 0.444hidden_inputs = [-0.35732982 -0.71979363 -0.0427763   0.3440054  -0.47113825 -0.27512146]
hidden_outputs = [ 0.41160609  0.32743843  0.48930756  0.58516315  0.38434687  0.43165022]
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Progress: 4.1% ... Training loss: 0.274 ... Validation loss: 0.442hidden_inputs = [-0.38178788  0.39133935 -0.23403584 -0.25557366 -0.43582545 -0.16359998]
hidden_outputs = [ 0.40569576  0.59660508  0.44175664  0.43645211  0.39273613  0.45919099]
final_inputs = [ 0.44049904]
final_outputs = [ 0.44049904]
error = [-0.38240845]
output_error_term = [-0.38240845]
hidden_error = [ 0.3805901   0.18321881  0.4319099   0.34930523 -1.06088899 -0.78130509]
hidden_error_term = [ 0.09176283  0.04409481  0.10651231  0.0859157  -0.25301615 -0.19402511]
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Progress: 4.1% ... Training loss: 0.272 ... Validation loss: 0.447hidden_inputs = [ 0.47876077 -0.02405411  0.03393012 -0.26197405 -1.131019    0.19858033]
hidden_outputs = [ 0.61745521  0.49398676  0.50848172  0.4348785   0.2439731   0.54948258]
final_inputs = [-0.04317374]
final_outputs = [-0.04317374]
error = [-0.26259737]
output_error_term = [-0.26259737]
hidden_error = [ 0.26318239  0.12806216  0.29834734  0.2417341  -0.72739231 -0.5346703 ]
hidden_error_term = [ 0.06216481  0.03201091  0.07456537  0.05940838 -0.13416767 -0.13235842]
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Progress: 4.1% ... Training loss: 0.270 ... Validation loss: 0.438hidden_inputs = [ 0.84099274  0.31304181  0.15340814 -0.58739988 -3.18556541 -0.62528818]
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Progress: 4.2% ... Training loss: 0.270 ... Validation loss: 0.436hidden_inputs = [-0.49078423 -0.33607021  0.03450168 -0.51758631 -0.35903233  0.12438287]
hidden_outputs = [ 0.37970884  0.41676438  0.50862456  0.37341681  0.41119383  0.53105569]
final_inputs = [ 0.6826776]
final_outputs = [ 0.6826776]
error = [-1.26410151]
output_error_term = [-1.26410151]
hidden_error = [ 1.29253699  0.62955326  1.45865129  1.18267482 -3.50151753 -2.56069379]
hidden_error_term = [ 0.30443129  0.15302666  0.36455432  0.27671835 -0.84776454 -0.63770377]
delta_weights_i_h = [[ 0.29189808  0.13089018  0.22223106  0.15152569 -0.24035306 -0.33893243]
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delta_weights_h_o = [[ 3.18956835]
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self.weights_hidden_to_output = [[-1.00754352]
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self.weights_input_to_hidden = [[-0.15387844 -0.28682426 -0.30912089 -0.4449155   0.39837887  0.11392181]
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Progress: 4.2% ... Training loss: 0.268 ... Validation loss: 0.438hidden_inputs = [ 0.44215076  0.11376841  0.63517731  0.0463123  -1.85889692 -0.36640329]
hidden_outputs = [ 0.60877139  0.52841146  0.65366247  0.51157601  0.13483168  0.4094104 ]
final_inputs = [-0.88127733]
final_outputs = [-0.88127733]
error = [-0.14119106]
output_error_term = [-0.14119106]
hidden_error = [ 0.14225614  0.06901891  0.16034669  0.13015676 -0.3911505  -0.28651344]
hidden_error_term = [ 0.03388097  0.01719902  0.03630054  0.03252175 -0.04562853 -0.06927709]
delta_weights_i_h = [[ 0.14523563  0.11687211  0.22047957  0.1241947   0.08418353 -0.26420473]
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Progress: 4.2% ... Training loss: 0.267 ... Validation loss: 0.437hidden_inputs = [ 0.29199999  0.39741529  1.08219383  0.55994124 -1.46580905 -0.49601893]
hidden_outputs = [ 0.57248569  0.5980665   0.74690892  0.63643894  0.18758045  0.37847669]
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final_outputs = [-1.01765813]
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Progress: 4.2% ... Training loss: 0.273 ... Validation loss: 0.442hidden_inputs = [ 0.09656157 -0.72937062  0.04874381 -0.05256647  0.70344836 -0.39992424]
hidden_outputs = [ 0.52412165  0.32533286  0.51218354  0.48686141  0.66895187  0.40133054]
final_inputs = [ 0.9127615]
final_outputs = [ 0.9127615]
error = [-0.43567865]
output_error_term = [-0.43567865]
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 [ 0.06212147  0.16606616  0.07722622  0.1888237  -0.23856345 -0.07165054]
 [-0.03397819  0.00384742 -0.1528904   0.02068075 -0.28217641 -0.21236401]
 [ 0.10498523 -0.15540333  0.13348425 -0.01683143 -0.2090773  -0.17919825]
 [-0.21712809 -0.04282965  0.01609365  0.16420239 -0.36045106 -0.14065715]
 [ 0.20624913  0.13547379  0.2718701  -0.02767984 -0.25550382  0.09966939]
 [ 0.07826753 -0.12165668  0.16306346  0.11003534 -0.27629969  0.03623743]]
Progress: 4.2% ... Training loss: 0.271 ... Validation loss: 0.437hidden_inputs = [ 0.06271767  0.40499476  0.38106042  0.30554998 -3.498528   -0.46757606]
hidden_outputs = [ 0.51567428  0.59988711  0.59412884  0.57579869  0.02935414  0.38519012]
final_inputs = [-1.14502777]
final_outputs = [-1.14502777]
error = [ 0.12255937]
output_error_term = [ 0.12255937]
hidden_error = [-0.12295706 -0.05930503 -0.13920631 -0.11277582  0.34081652  0.24997138]
hidden_error_term = [-0.03070906 -0.01423455 -0.03356818 -0.02754601  0.00971071  0.0591979 ]
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delta_weights_h_o = [[-1.94665794]
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self.weights_hidden_to_output = [[-1.0123698 ]
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   -2.15507221e-01  -1.84446912e-01]
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Progress: 4.2% ... Training loss: 0.269 ... Validation loss: 0.441hidden_inputs = [-0.13553229 -0.41021081  0.43865384  0.06982208 -1.35199593  0.03496609]
hidden_outputs = [ 0.4661687   0.39886157  0.60793822  0.51744843  0.20554425  0.50874063]
final_inputs = [-0.24317244]
final_outputs = [-0.24317244]
error = [ 0.23510636]
output_error_term = [ 0.23510636]
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Progress: 4.2% ... Training loss: 0.267 ... Validation loss: 0.440hidden_inputs = [ 0.06560839  0.6512344   0.32941181 -0.30183779 -3.85234225 -0.70876517]
hidden_outputs = [ 0.51639622  0.65728858  0.58161626  0.42510828  0.02078861  0.32987175]
final_inputs = [-1.1509629]
final_outputs = [-1.1509629]
error = [ 0.11195534]
output_error_term = [ 0.11195534]
hidden_error = [-0.11180058 -0.05449848 -0.12670869 -0.1025448   0.31169809  0.22889772]
hidden_error_term = [-0.02792009 -0.01227634 -0.03083314 -0.02506105  0.00634506  0.0505993 ]
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Progress: 4.2% ... Training loss: 0.284 ... Validation loss: 0.456hidden_inputs = [ 0.43131975 -0.25415244  0.81606189 -0.46366766 -2.47530624 -0.83782749]
hidden_outputs = [ 0.60618877  0.43680171  0.69339975  0.38611612  0.07760754  0.30199254]
final_inputs = [-1.209056]
final_outputs = [-1.209056]
error = [ 0.17556149]
output_error_term = [ 0.17556149]
hidden_error = [-0.18103093 -0.09124271 -0.20509878 -0.16646151  0.48333694  0.35202372]
hidden_error_term = [-0.04321642 -0.02244625 -0.04360329 -0.03945645  0.03459949  0.07420415]
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Progress: 4.2% ... Training loss: 0.282 ... Validation loss: 0.448hidden_inputs = [ 0.15453134 -0.1476375   0.27108054  0.21896332 -0.75179105 -0.72625668]
hidden_outputs = [ 0.53855614  0.46315752  0.56735816  0.55452316  0.32043116  0.32601671]
final_inputs = [-0.30760736]
final_outputs = [-0.30760736]
error = [-0.33446017]
output_error_term = [-0.33446017]
hidden_error = [ 0.32648319  0.15758817  0.37077253  0.29919333 -0.93201555 -0.68572831]
hidden_error_term = [ 0.08113546  0.03918314  0.09101089  0.0739089  -0.20295108 -0.15067495]
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Progress: 4.2% ... Training loss: 0.293 ... Validation loss: 0.462hidden_inputs = [-0.08019627 -0.00259591 -0.2013893  -0.67735293 -2.04273693  0.4090504 ]
hidden_outputs = [ 0.47996167  0.49935102  0.44982215  0.33685236  0.11478833  0.60086016]
final_inputs = [-0.09375405]
final_outputs = [-0.09375405]
error = [-0.2450954]
output_error_term = [-0.2450954]
hidden_error = [ 0.25432211  0.12823074  0.28633963  0.23235881 -0.67172596 -0.48777497]
hidden_error_term = [ 0.06347841  0.03205763  0.07086396  0.05190497 -0.0682554  -0.11698172]
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Progress: 4.2% ... Training loss: 0.321 ... Validation loss: 0.465hidden_inputs = [ 0.5005039   0.3654048  -0.54320267 -1.02050798 -1.93378983  0.36764677]
hidden_outputs = [ 0.62257774  0.59034815  0.36744287  0.26492846  0.1263317   0.59089023]
final_inputs = [ 0.08732255]
final_outputs = [ 0.08732255]
error = [-0.1615453]
output_error_term = [-0.1615453]
hidden_error = [ 0.15435877  0.07282734  0.17614297  0.1416017  -0.4548204  -0.33505197]
hidden_error_term = [ 0.0362704   0.01761236  0.04094067  0.02757571 -0.05019944 -0.08099512]
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Progress: 4.3% ... Training loss: 0.271 ... Validation loss: 0.445hidden_inputs = [-0.06512818 -0.07166502  0.11898269  0.89573988  0.59953124 -0.61171306]
hidden_outputs = [ 0.48372371  0.48209141  0.52971063  0.71007326  0.64554905  0.35166852]
final_inputs = [ 0.4941485]
final_outputs = [ 0.4941485]
error = [-0.75581516]
output_error_term = [-0.75581516]
hidden_error = [ 0.76644873  0.38011718  0.86965472  0.70121429 -2.09158501 -1.52371817]
hidden_error_term = [ 0.19140914  0.09490739  0.21664602  0.14435844 -0.47858701 -0.34740435]
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Progress: 4.3% ... Training loss: 0.289 ... Validation loss: 0.458hidden_inputs = [-0.08154755 -0.33199333  0.41549633 -0.06778225 -2.02503835 -0.1581432 ]
hidden_outputs = [ 0.4796244   0.41775569  0.60240506  0.48306092  0.11659902  0.46054639]
final_inputs = [-0.63163852]
final_outputs = [-0.63163852]
error = [ 0.22111934]
output_error_term = [ 0.22111934]
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hidden_error_term = [-0.05689965 -0.02790484 -0.06187964 -0.05228133  0.06263034  0.10976622]
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Progress: 4.3% ... Training loss: 0.280 ... Validation loss: 0.458hidden_inputs = [ 0.16572467  0.15219358 -0.14935621 -0.47629894 -2.24474865 -0.45821799]
hidden_outputs = [ 0.5413366   0.53797512  0.4627302   0.38312646  0.0958034   0.38740865]
final_inputs = [-0.58307122]
final_outputs = [-0.58307122]
error = [-0.12515298]
output_error_term = [-0.12515298]
hidden_error = [ 0.12267992  0.05896059  0.13990439  0.1125354  -0.34993709 -0.25679723]
hidden_error_term = [ 0.03046035  0.01465512  0.03478176  0.02659668 -0.03031334 -0.06094394]
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Progress: 4.3% ... Training loss: 0.320 ... Validation loss: 0.470hidden_inputs = [ 0.42839552 -0.24479115  0.13566558 -0.05549822  0.63710062 -0.87985719]
hidden_outputs = [ 0.60549047  0.43910599  0.53386447  0.48612901  0.65409776  0.29320737]
final_inputs = [ 0.40018638]
final_outputs = [ 0.40018638]
error = [ 0.1981837]
output_error_term = [ 0.1981837]
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Progress: 4.3% ... Training loss: 0.267 ... Validation loss: 0.441hidden_inputs = [-0.03776685 -0.40643397 -0.29320582  0.17931491  1.16386873  0.06589774]
hidden_outputs = [ 0.49055941  0.3997675   0.42721921  0.54470899  0.76203497  0.51646848]
final_inputs = [ 1.50282315]
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error = [ 0.01071423]
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Progress: 4.3% ... Training loss: 0.277 ... Validation loss: 0.441hidden_inputs = [ 0.57653692  0.32063357 -0.17085388 -0.88493034 -2.85559952  0.16657086]
hidden_outputs = [ 0.64027016  0.57947865  0.45739013  0.29215713  0.05439259  0.5415467 ]
final_inputs = [-0.41602558]
final_outputs = [-0.41602558]
error = [-0.08821555]
output_error_term = [-0.08821555]
hidden_error = [ 0.08648102  0.04190125  0.09808731  0.07957246 -0.24663843 -0.18031445]
hidden_error_term = [ 0.01991868  0.01021063  0.02434374  0.01645569 -0.01268561 -0.04476737]
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delta_weights_h_o = [[-5.11315412]
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self.weights_hidden_to_output = [[-1.00430547]
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Progress: 4.3% ... Training loss: 0.269 ... Validation loss: 0.439hidden_inputs = [ 0.65250069  0.11428414 -0.28754947 -0.76636637 -3.94190186 -0.52873407]
hidden_outputs = [ 0.65757377  0.52853998  0.4286039   0.31726566  0.01904164  0.37081219]
final_inputs = [-0.90313078]
final_outputs = [-0.90313078]
error = [-0.03112872]
output_error_term = [-0.03112872]
hidden_error = [ 0.03126274  0.01550259  0.03537557  0.02887546 -0.08632857 -0.06288212]
hidden_error_term = [ 0.00703945  0.00386302  0.00866357  0.00625466 -0.00161254 -0.01467106]
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delta_weights_h_o = [[ 0.19207362]
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self.weights_hidden_to_output = [[-1.00340513]
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Progress: 4.3% ... Training loss: 0.270 ... Validation loss: 0.438hidden_inputs = [ 0.6774225  -0.60999932  0.01463272  0.3778574  -1.30303374 -0.75800581]
hidden_outputs = [ 0.66316318  0.35205935  0.50365812  0.59335623  0.21365489  0.31907938]
final_inputs = [-0.71919952]
final_outputs = [-0.71919952]
error = [-0.08825969]
output_error_term = [-0.08825969]
hidden_error = [ 0.08856022  0.04364178  0.09991261  0.08181144 -0.24513872 -0.17897769]
hidden_error_term = [ 0.01978239  0.00995528  0.02497681  0.01973984 -0.04118489 -0.03888608]
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Progress: 4.3% ... Training loss: 0.273 ... Validation loss: 0.451hidden_inputs = [ 0.2511891  -0.39817319  0.30765903 -0.19982574 -1.98080535  0.09208942]
hidden_outputs = [ 0.56246916  0.40175133  0.57631375  0.45020914  0.12123301  0.5230061 ]
final_inputs = [-0.43511959]
final_outputs = [-0.43511959]
error = [ 0.50423629]
output_error_term = [ 0.50423629]
hidden_error = [-0.50442402 -0.24972819 -0.56825493 -0.46378518  1.39341232  1.01722406]
hidden_error_term = [-0.12413754 -0.06002147 -0.13875434 -0.11479651  0.14844797  0.25376762]
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delta_weights_h_o = [[ 4.21345213]
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self.weights_hidden_to_output = [[-0.98062176]
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Progress: 4.3% ... Training loss: 0.270 ... Validation loss: 0.446hidden_inputs = [ 0.07803559 -0.61988733  0.34707049  0.26022859 -1.36813398 -0.73097143]
hidden_outputs = [ 0.519499    0.34980708  0.585907    0.56469248  0.2029215   0.32498159]
final_inputs = [-0.60726836]
final_outputs = [-0.60726836]
error = [ 0.18572308]
output_error_term = [ 0.18572308]
hidden_error = [-0.18212409 -0.08827716 -0.20539249 -0.16803619  0.5167956   0.37869913]
hidden_error_term = [-0.04546178 -0.02007794 -0.04983232 -0.0413058   0.08358878  0.08307468]
delta_weights_i_h = [[ 0.99680651  0.49714505  1.11549918  0.77952903 -1.56258639 -2.195585  ]
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delta_weights_h_o = [[-7.62209384]
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self.weights_hidden_to_output = [[-1.01635033]
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Progress: 4.4% ... Training loss: 0.285 ... Validation loss: 0.460hidden_inputs = [-0.1961816   0.11767076  0.62356496 -0.05170149 -0.55677386 -0.41959431]
hidden_outputs = [ 0.4511113   0.52938379  0.65102891  0.48707751  0.36429425  0.39661383]
final_inputs = [-0.13084742]
final_outputs = [-0.13084742]
error = [ 0.34330358]
output_error_term = [ 0.34330358]
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Progress: 4.4% ... Training loss: 0.303 ... Validation loss: 0.462hidden_inputs = [-0.02552559 -0.1752247  -0.39843146 -0.91137556 -1.27810333  0.77871035]
hidden_outputs = [ 0.49361895  0.45630556  0.40168926  0.28671844  0.21787325  0.6854021 ]
final_inputs = [ 0.64939888]
final_outputs = [ 0.64939888]
error = [-0.53617773]
output_error_term = [-0.53617773]
hidden_error = [ 0.51444126  0.24811     0.58290496  0.47493558 -1.51043564 -1.10384995]
hidden_error_term = [ 0.12858937  0.06155381  0.14009246  0.09712954 -0.25738503 -0.23801882]
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Progress: 4.4% ... Training loss: 0.270 ... Validation loss: 0.436hidden_inputs = [ 0.21821025 -0.18662418  0.52016154 -0.17642221 -2.31923463 -0.59715871]
hidden_outputs = [ 0.55433713  0.4534789   0.62718554  0.45600849  0.08954244  0.354994  ]
final_inputs = [-0.95959577]
final_outputs = [-0.95959577]
error = [ 0.26791073]
output_error_term = [ 0.26791073]
hidden_error = [-0.27061958 -0.13462773 -0.30446181 -0.25056055  0.74731499  0.54162799]
hidden_error_term = [-0.06685589 -0.03336557 -0.07119043 -0.06215524  0.06092455  0.12401833]
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Progress: 4.4% ... Training loss: 0.268 ... Validation loss: 0.436hidden_inputs = [  8.29393037e-01   4.90588632e-04   1.50644147e-01  -9.03772444e-02
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final_inputs = [-1.31511232]
final_outputs = [-1.31511232]
error = [ 0.28713087]
output_error_term = [ 0.28713087]
hidden_error = [-0.28494902 -0.14046635 -0.32250186 -0.26323547  0.80171293  0.5803659 ]
hidden_error_term = [-0.06026533 -0.03511659 -0.08016977 -0.06567467  0.01853362  0.12065525]
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Progress: 4.4% ... Training loss: 0.273 ... Validation loss: 0.444hidden_inputs = [ 0.23583092  0.02314365 -0.1691597  -0.81286536 -3.00304282  0.14839943]
hidden_outputs = [ 0.55868599  0.50578565  0.45781063  0.30728024  0.0472886   0.53703192]
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final_outputs = [-0.41394485]
error = [ 0.35626127]
output_error_term = [ 0.35626127]
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hidden_error_term = [-0.08817869 -0.04492449 -0.10050692 -0.07054254  0.04461606  0.17760086]
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Progress: 4.4% ... Training loss: 0.269 ... Validation loss: 0.441hidden_inputs = [ 0.25580366 -0.36828452  0.37753122  0.68266648 -0.61519699 -0.29355171]
hidden_outputs = [ 0.56360446  0.40895561  0.59327753  0.66433357  0.35087461  0.42713457]
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error = [ 1.31862243]
output_error_term = [ 1.31862243]
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Progress: 4.4% ... Training loss: 0.267 ... Validation loss: 0.442hidden_inputs = [ 0.19841992 -0.49235933  0.41146559 -0.14038195 -1.18784248 -0.86338747]
hidden_outputs = [ 0.54944287  0.37933793  0.60143925  0.46496204  0.23364503  0.29663209]
final_inputs = [-0.57801995]
final_outputs = [-0.57801995]
error = [-0.33970038]
output_error_term = [-0.33970038]
hidden_error = [ 0.33477691  0.16545432  0.37996065  0.31075902 -0.94501005 -0.68289234]
hidden_error_term = [ 0.08287583  0.03895467  0.0910804   0.07730825 -0.1692088  -0.14247968]
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Progress: 4.4% ... Training loss: 0.266 ... Validation loss: 0.445hidden_inputs = [ 0.27616872 -0.1515654   0.48092499  0.04782724 -2.18992556 -0.58898568]
hidden_outputs = [ 0.56860669  0.46218102  0.61796627  0.51195453  0.10065883  0.35686762]
final_inputs = [-0.92514901]
final_outputs = [-0.92514901]
error = [ 0.12871591]
output_error_term = [ 0.12871591]
hidden_error = [-0.12549694 -0.06174173 -0.1432416  -0.11658912  0.35940574  0.26015896]
hidden_error_term = [-0.03078354 -0.01534713 -0.03381704 -0.02913062  0.03253579  0.05970989]
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Progress: 4.4% ... Training loss: 0.287 ... Validation loss: 0.446hidden_inputs = [ 0.3444817  -0.15601885 -0.49308445 -0.75019517 -2.74950147  0.03090941]
hidden_outputs = [ 0.58527877  0.46107422  0.37916722  0.32077877  0.06011481  0.50772674]
final_inputs = [-0.27045572]
final_outputs = [-0.27045572]
error = [-0.17865485]
output_error_term = [-0.17865485]
hidden_error = [ 0.17203135  0.08320395  0.19653522  0.15913314 -0.50512778 -0.36620457]
hidden_error_term = [ 0.04175675  0.02067491  0.04626428  0.03467189 -0.02854024 -0.09152928]
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Progress: 4.5% ... Training loss: 0.274 ... Validation loss: 0.442hidden_inputs = [ 0.05395208  0.55856887 -0.23957807 -0.58735531 -2.60233161  0.15365731]
hidden_outputs = [ 0.51348475  0.63612134  0.44039033  0.3572419   0.06898851  0.53833892]
final_inputs = [-0.40143315]
final_outputs = [-0.40143315]
error = [-0.20755604]
output_error_term = [-0.20755604]
hidden_error = [ 0.2090641   0.10400246  0.23780247  0.19462373 -0.57832227 -0.41710824]
hidden_error_term = [ 0.05222801  0.02407355  0.05860563  0.04468952 -0.03714512 -0.10366396]
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Progress: 4.5% ... Training loss: 0.267 ... Validation loss: 0.444hidden_inputs = [-0.24501676 -0.06166919 -0.20636138 -0.45986867 -0.66606769  0.08672635]
hidden_outputs = [ 0.43905042  0.48458759  0.44859196  0.38701698  0.33937791  0.52166801]
final_inputs = [ 0.49907881]
final_outputs = [ 0.49907881]
error = [ 2.19976562]
output_error_term = [ 2.19976562]
hidden_error = [-2.15690085 -1.0514169  -2.4560928  -2.00346403  6.17659712  4.47661281]
hidden_error_term = [-0.53121265 -0.26260447 -0.60753227 -0.47529146  1.38479643  1.11705142]
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Progress: 4.5% ... Training loss: 0.268 ... Validation loss: 0.448hidden_inputs = [-0.88283582 -0.13139046 -0.39748304  0.02093713 -0.66522917  0.57638199]
hidden_outputs = [ 0.29259047  0.46719956  0.40191722  0.50523409  0.33956593  0.64023448]
final_inputs = [ 0.82032367]
final_outputs = [ 0.82032367]
error = [-1.27494729]
output_error_term = [-1.27494729]
hidden_error = [ 1.25747248  0.61930925  1.43245901  1.17029456 -3.57294445 -2.58793833]
hidden_error_term = [ 0.26027327  0.15416102  0.34433417  0.29254158 -0.80127177 -0.59609094]
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Progress: 4.5% ... Training loss: 0.272 ... Validation loss: 0.444hidden_inputs = [ 0.64434745  0.07445756 -0.40679184 -0.89386456 -2.90481773 -0.0420478 ]
hidden_outputs = [ 0.65573555  0.5186058   0.39968163  0.29031296  0.05191592  0.4894896 ]
final_inputs = [-0.51647754]
final_outputs = [-0.51647754]
error = [-0.32406001]
output_error_term = [-0.32406001]
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hidden_error_term = [ 0.07352983  0.04074867  0.08850094  0.06240647 -0.04457054 -0.1629601 ]
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Progress: 4.5% ... Training loss: 0.278 ... Validation loss: 0.453hidden_inputs = [ 0.26052129  0.10949556  0.7985047   0.57114216 -2.4487462  -0.55386294]
hidden_outputs = [ 0.56476443  0.52734657  0.68965453  0.63902668  0.07953029  0.36496864]
final_inputs = [-1.1688565]
final_outputs = [-1.1688565]
error = [ 0.16292727]
output_error_term = [ 0.16292727]
hidden_error = [-0.15866848 -0.0775536  -0.18027891 -0.14695969  0.46064006  0.33338708]
hidden_error_term = [-0.0390016  -0.0193304  -0.0385853  -0.03389942  0.03372126  0.07726797]
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Progress: 4.5% ... Training loss: 0.269 ... Validation loss: 0.438hidden_inputs = [ 0.0689016   0.24549744  0.017138   -0.690754   -1.24403163 -0.04311833]
hidden_outputs = [ 0.51721859  0.56106796  0.50428439  0.33386536  0.223735    0.48922209]
final_inputs = [-0.07156703]
final_outputs = [-0.07156703]
error = [-0.23420408]
output_error_term = [-0.23420408]
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Progress: 4.5% ... Training loss: 0.270 ... Validation loss: 0.439hidden_inputs = [ 0.0612673  -0.35551508 -0.29342919  0.77270012 -1.34018779 -0.50383323]
hidden_outputs = [ 0.51531204  0.41204567  0.42716455  0.68410469  0.20747918  0.37664027]
final_inputs = [-0.51159895]
final_outputs = [-0.51159895]
error = [-0.51086945]
output_error_term = [-0.51086945]
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Progress: 4.5% ... Training loss: 0.277 ... Validation loss: 0.448hidden_inputs = [ 0.50666039  0.46494413  0.24640925 -0.64476939 -3.04537538 -0.74622596]
hidden_outputs = [ 0.62402327  0.6141864   0.5612925   0.34416921  0.04541755  0.3216442 ]
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final_outputs = [-1.1303667]
error = [ 0.20162026]
output_error_term = [ 0.20162026]
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delta_weights_h_o = [[ 7.64322624]
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self.weights_hidden_to_output = [[-0.97223868]
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self.weights_input_to_hidden = [[-0.1553688  -0.29056242 -0.31090111 -0.45351042  0.46431841  0.1246975 ]
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Progress: 4.5% ... Training loss: 0.274 ... Validation loss: 0.444hidden_inputs = [ 0.79583425  0.16378703  0.14980025 -1.44981018 -2.21994046  0.17214961]
hidden_outputs = [ 0.68908268  0.54085547  0.53738019  0.19003078  0.09797407  0.54293143]
final_inputs = [-0.30452763]
final_outputs = [-0.30452763]
error = [-0.06188709]
output_error_term = [-0.06188709]
hidden_error = [ 0.06016903  0.0290677   0.06842891  0.05547139 -0.17458533 -0.12625039]
hidden_error_term = [ 0.01289108  0.00721841  0.01701161  0.00853811 -0.015429   -0.0313299 ]
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Progress: 4.5% ... Training loss: 0.270 ... Validation loss: 0.447hidden_inputs = [ 0.44545356  0.20422703 -0.10635255 -1.33581636 -2.21838943  0.20502469]
hidden_outputs = [ 0.60955774  0.55088004  0.4734369   0.2081989   0.09811122  0.55107738]
final_inputs = [-0.22757159]
final_outputs = [-0.22757159]
error = [ 0.36284496]
output_error_term = [ 0.36284496]
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Progress: 4.5% ... Training loss: 0.271 ... Validation loss: 0.447hidden_inputs = [ 0.20346615 -0.43687988  0.03550419  0.56084781 -1.23275766 -0.68007569]
hidden_outputs = [ 0.55069178  0.39248468  0.50887512  0.63664868  0.22569913  0.33624441]
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error = [-0.27635345]
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Progress: 4.6% ... Training loss: 0.270 ... Validation loss: 0.450hidden_inputs = [ 0.03265197 -0.74463286  0.15630367 -0.6686141  -0.30649655  0.20253223]
hidden_outputs = [ 0.50816227  0.3219919   0.53899656  0.33880724  0.42397012  0.55046069]
final_inputs = [ 0.74245619]
final_outputs = [ 0.74245619]
error = [-1.48927179]
output_error_term = [-1.48927179]
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Progress: 4.6% ... Training loss: 0.269 ... Validation loss: 0.445hidden_inputs = [-0.02386863 -0.70081135  0.35653064  0.23197973 -1.42664366 -0.62162278]
hidden_outputs = [ 0.49403313  0.33163236  0.58820034  0.55773624  0.19362218  0.34941247]
final_inputs = [-0.54468341]
final_outputs = [-0.54468341]
error = [ 0.2389123]
output_error_term = [ 0.2389123]
hidden_error = [-0.23540123 -0.11212241 -0.2663037  -0.21599586  0.67464469  0.48604542]
hidden_error_term = [-0.05884193 -0.0248522  -0.06450427 -0.05327895  0.10533405  0.1104895 ]
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delta_weights_h_o = [[-6.20245247]
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self.weights_hidden_to_output = [[-1.01437791]
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Progress: 4.6% ... Training loss: 0.274 ... Validation loss: 0.442hidden_inputs = [-0.14734385  0.26182089 -0.33411501 -0.90714326 -2.73058975  0.56329407]
hidden_outputs = [ 0.46323054  0.56508385  0.41723972  0.28758477  0.06119227  0.63721438]
final_inputs = [-0.0436148]
final_outputs = [-0.0436148]
error = [-0.89615776]
output_error_term = [-0.89615776]
hidden_error = [ 0.90904263  0.442789    1.02598542  0.83770911 -2.50805209 -1.80119023]
hidden_error_term = [ 0.22603164  0.10882164  0.24946911  0.17162965 -0.14408202 -0.41638513]
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Progress: 4.6% ... Training loss: 0.266 ... Validation loss: 0.441hidden_inputs = [ 0.01324235 -0.25426906  0.76139432 -0.39423386 -2.83443648 -0.58411841]
hidden_outputs = [ 0.50331054  0.43677302  0.68165638  0.4026985   0.05549141  0.3579855 ]
final_inputs = [-0.95067353]
final_outputs = [-0.95067353]
error = [ 0.31411906]
output_error_term = [ 0.31411906]
hidden_error = [-0.31048608 -0.14809106 -0.35232803 -0.28608554  0.88603007  0.63838963]
hidden_error_term = [-0.07761812 -0.03643075 -0.07645552 -0.06881285  0.04643871  0.14672229]
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Progress: 4.6% ... Training loss: 0.274 ... Validation loss: 0.437hidden_inputs = [ 0.10654041 -0.22896925  0.39799661  1.0339921  -1.02214484 -0.53140235]
hidden_outputs = [ 0.52660994  0.44300647  0.59820623  0.73768911  0.26460982  0.37018987]
final_inputs = [-0.5627214]
final_outputs = [-0.5627214]
error = [ 0.19630668]
output_error_term = [ 0.19630668]
hidden_error = [-0.19375529 -0.09258499 -0.22004647 -0.17723025  0.55591373  0.39940854]
hidden_error_term = [-0.04830163 -0.02284551 -0.05288939 -0.03429474  0.10817607  0.09312183]
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Progress: 4.6% ... Training loss: 0.267 ... Validation loss: 0.431hidden_inputs = [-0.00824189 -0.40722793 -0.41797833 -0.79754425 -1.29334785  0.05134905]
hidden_outputs = [ 0.49793954  0.399577    0.39700062  0.31055107  0.21528669  0.51283444]
final_inputs = [ 0.20705471]
final_outputs = [ 0.20705471]
error = [ 0.56773316]
output_error_term = [ 0.56773316]
hidden_error = [-0.57105145 -0.27807044 -0.64629367 -0.51926211  1.59929862  1.14372224]
hidden_error_term = [-0.14276044 -0.06671333 -0.15471697 -0.11117875  0.27018284  0.28574216]
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Progress: 4.6% ... Training loss: 0.270 ... Validation loss: 0.439hidden_inputs = [ 0.34691084  0.13437941 -0.09864615 -0.56129346 -2.9383011   0.28464747]
hidden_outputs = [ 0.58586826  0.53354439  0.47535844  0.36324823  0.05029236  0.57068524]
final_inputs = [-0.44741403]
final_outputs = [-0.44741403]
error = [-0.24978406]
output_error_term = [-0.24978406]
hidden_error = [ 0.25163334  0.12356664  0.2859558   0.22971042 -0.69966031 -0.50076855]
hidden_error_term = [ 0.06105295  0.03075262  0.07131532  0.05313178 -0.0334179  -0.1226901 ]
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Progress: 4.6% ... Training loss: 0.265 ... Validation loss: 0.438hidden_inputs = [-0.13575571  0.3286885   0.19515773  0.21825739  0.02283892 -0.14003762]
hidden_outputs = [ 0.4661131   0.58144024  0.54863517  0.55434877  0.50570948  0.4650477 ]
final_inputs = [ 0.50558297]
final_outputs = [ 0.50558297]
error = [-0.13876125]
output_error_term = [-0.13876125]
hidden_error = [ 0.13656516  0.06580918  0.15599739  0.12549475 -0.38970738 -0.27986169]
hidden_error_term = [ 0.03398447  0.01601582  0.03863035  0.031003   -0.09741414 -0.06962353]
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Progress: 4.6% ... Training loss: 0.268 ... Validation loss: 0.444hidden_inputs = [-0.24914985 -0.42898258 -0.06993578  0.2078951  -0.41279223  0.40913212]
hidden_outputs = [ 0.43803276  0.39436931  0.48252318  0.55178739  0.39824279  0.60087976]
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final_outputs = [ 0.64580883]
error = [-1.46429415]
output_error_term = [-1.46429415]
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Progress: 4.7% ... Training loss: 0.281 ... Validation loss: 0.461hidden_inputs = [-0.38581536 -0.00623999  0.23013145 -0.01156958 -1.4299974  -0.15599842]
hidden_outputs = [ 0.40472507  0.49844001  0.55728029  0.49710764  0.19309909  0.46107929]
final_inputs = [-0.30755509]
final_outputs = [-0.30755509]
error = [ 0.09550593]
output_error_term = [ 0.09550593]
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hidden_error_term = [-0.02315478 -0.01190084 -0.02691893 -0.02218231  0.04124037  0.04691593]
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Progress: 4.7% ... Training loss: 0.266 ... Validation loss: 0.449hidden_inputs = [-0.17908042  0.04215292  0.11098934 -0.52403413  1.4741795   0.72792349]
hidden_outputs = [ 0.45534916  0.51053667  0.52771889  0.3719094   0.81369182  0.67434943]
final_inputs = [ 2.00298199]
final_outputs = [ 2.00298199]
error = [ 0.77304523]
output_error_term = [ 0.77304523]
hidden_error = [-0.75411044 -0.36545948 -0.85848563 -0.69438177  2.14936055  1.54330787]
hidden_error_term = [-0.18702414 -0.0913243  -0.2139618  -0.16220258  0.32583756  0.33891392]
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delta_weights_h_o = [[ 4.26050442]
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self.weights_hidden_to_output = [[-0.95553512]
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Progress: 4.7% ... Training loss: 0.271 ... Validation loss: 0.444hidden_inputs = [-0.22146692 -0.26050909 -0.3645602  -1.04957937 -1.88974878  0.80034213]
hidden_outputs = [ 0.44485847  0.43523857  0.40985612  0.25930588  0.13127312  0.69004766]
final_inputs = [ 0.45913165]
final_outputs = [ 0.45913165]
error = [-1.33274753]
output_error_term = [-1.33274753]
hidden_error = [ 1.27348707  0.60629986  1.4580434   1.17701464 -3.73070202 -2.68875211]
hidden_error_term = [ 0.31449962  0.14903212  0.35266291  0.2260649  -0.42545107 -0.57507537]
delta_weights_i_h = [[ 0.73628612  0.3421665   0.82272743  0.70886707 -1.12122376 -1.58180287]
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delta_weights_h_o = [[-6.03210999]
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Progress: 4.7% ... Training loss: 0.267 ... Validation loss: 0.448hidden_inputs = [ 0.39599833  0.36445692 -0.20152334 -0.28696776 -3.58820299 -0.43070841]
hidden_outputs = [ 0.59772584  0.5901189   0.44978898  0.42874637  0.02690413  0.39395718]
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final_outputs = [-0.90148046]
error = [-0.126501]
output_error_term = [-0.126501]
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delta_weights_h_o = [[ 0.20771933]
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self.weights_hidden_to_output = [[-0.98283695]
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self.weights_input_to_hidden = [[-0.12800019 -0.27808762 -0.27889108 -0.43087801  0.44494201  0.0769275 ]
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Progress: 4.7% ... Training loss: 0.267 ... Validation loss: 0.453hidden_inputs = [-0.13629393 -0.49208825  0.20476347  0.0965661   0.43359816 -0.09053036]
hidden_outputs = [ 0.46597917  0.37940175  0.55101275  0.52412278  0.60673255  0.47738285]
final_inputs = [ 0.90807302]
final_outputs = [ 0.90807302]
error = [-0.42547712]
output_error_term = [-0.42547712]
hidden_error = [ 0.41817463  0.20431487  0.47520093  0.3848297  -1.18346452 -0.84677471]
hidden_error_term = [ 0.10405966  0.04810717  0.11756362  0.09598349 -0.28238429 -0.21126052]
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Progress: 4.7% ... Training loss: 0.284 ... Validation loss: 0.452hidden_inputs = [ 0.03207343  0.30483288 -0.27233525 -0.05866195 -3.43580024  0.0865934 ]
hidden_outputs = [ 0.50801767  0.57562353  0.43233388  0.48533872  0.03119516  0.52163483]
final_inputs = [-0.48865013]
final_outputs = [-0.48865013]
error = [ 0.01197428]
output_error_term = [ 0.01197428]
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hidden_error_term = [-0.00283959 -0.00133128 -0.00319394 -0.0026146   0.00101934  0.006081  ]
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Progress: 4.7% ... Training loss: 0.267 ... Validation loss: 0.449hidden_inputs = [-0.25561525 -0.22235174  0.15945802  0.08144615 -0.48826513 -0.14178494]
hidden_outputs = [ 0.43644188  0.44463996  0.53978025  0.52035029  0.38030234  0.46461303]
final_inputs = [ 0.27319716]
final_outputs = [ 0.27319716]
error = [-1.1523261]
output_error_term = [-1.1523261]
hidden_error = [ 1.13020774  0.55432138  1.2910272   1.04584844 -3.21834939 -2.30662571]
hidden_error_term = [ 0.27798631  0.1368815   0.32071379  0.26102899 -0.75847635 -0.57376798]
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Progress: 4.7% ... Training loss: 0.265 ... Validation loss: 0.440hidden_inputs = [-0.5627297  -0.66230499 -0.239183    0.20673448  0.48381881  0.71479242]
hidden_outputs = [ 0.3629161   0.34022202  0.4404877   0.55150033  0.61864922  0.67145924]
final_inputs = [ 1.57621632]
final_outputs = [ 1.57621632]
error = [-0.75181094]
output_error_term = [-0.75181094]
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Progress: 4.7% ... Training loss: 0.268 ... Validation loss: 0.438hidden_inputs = [-0.10839466 -0.67490333 -0.40582957 -0.33458071 -0.23469064 -0.2475135 ]
hidden_outputs = [ 0.47292784  0.33739977  0.39991253  0.41712649  0.44159517  0.43843561]
final_inputs = [ 0.67293244]
final_outputs = [ 0.67293244]
error = [-0.56522434]
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Progress: 4.7% ... Training loss: 0.268 ... Validation loss: 0.447hidden_inputs = [ 0.323887    0.13139751  0.53997841 -0.07166496 -2.20145614 -0.82936739]
hidden_outputs = [ 0.58027125  0.5328022   0.63180739  0.48209142  0.0996198   0.30377885]
final_inputs = [-1.09631452]
final_outputs = [-1.09631452]
error = [ 0.07935918]
output_error_term = [ 0.07935918]
hidden_error = [-0.07802217 -0.03860814 -0.08971637 -0.07207533  0.22212812  0.15848342]
hidden_error_term = [-0.01900281 -0.00961049 -0.02087043 -0.01799572  0.01992394  0.03351881]
delta_weights_i_h = [[-0.37784702 -0.14812974 -0.39726008 -0.24525505  1.08908449  0.764006  ]
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delta_weights_h_o = [[ 3.21036632]
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self.weights_hidden_to_output = [[-0.96810383]
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self.weights_input_to_hidden = [[-0.14663887 -0.28645743 -0.30046715 -0.44745963  0.50069783  0.11632328]
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Progress: 4.8% ... Training loss: 0.268 ... Validation loss: 0.439hidden_inputs = [ 0.2973428  -0.2702416   0.55766105  0.61700554 -1.07612818 -0.44722726]
hidden_outputs = [ 0.57379281  0.43284778  0.63591118  0.6495372   0.25423942  0.39002021]
final_inputs = [-0.55917186]
final_outputs = [-0.55917186]
error = [-0.09943484]
output_error_term = [-0.09943484]
hidden_error = [ 0.09626325  0.04729287  0.11057569  0.08937171 -0.27896458 -0.19882916]
hidden_error_term = [ 0.02354162  0.01160996  0.02560139  0.02034445 -0.05289217 -0.04730234]
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Progress: 4.8% ... Training loss: 0.266 ... Validation loss: 0.441hidden_inputs = [-0.58710157  0.25627508 -0.61998668 -0.57093188 -0.72312407  0.77517609]
hidden_outputs = [ 0.35730017  0.5637204   0.34978448  0.36102183  0.32670541  0.68463952]
final_inputs = [ 0.95190834]
final_outputs = [ 0.95190834]
error = [-0.27084242]
output_error_term = [-0.27084242]
hidden_error = [ 0.26291668  0.12926307  0.30266448  0.24471883 -0.75951128 -0.54146055]
hidden_error_term = [ 0.06037533  0.03179092  0.06883659  0.05645298 -0.16706893 -0.1169058 ]
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 [  8.56865985e-01   4.12520165e-01   9.96402862e-01   7.81609854e-01
   -2.12835980e+00  -1.75278728e+00]
 [ -2.66334420e-01  -1.37670948e-01  -2.52029201e-01  -2.30619322e-01
    6.01699185e-01   5.08868136e-01]
 [ -1.03583349e-01  -5.02825477e-02  -1.31029695e-01  -8.77786437e-02
    2.32933688e-02   2.02181418e-01]
 [  2.83153351e-01   1.56311039e-01   3.27456714e-01   2.07079358e-01
   -7.79259331e-01  -6.18593841e-01]
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    1.63311050e+00   1.27556593e+00]
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    3.93680261e-01   4.61518868e-01]
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    6.13584903e-01   7.76601695e-01]
 [  2.95904723e-01   1.46443970e-01   3.39748281e-01   2.42732617e-01
   -2.54430801e-01  -6.03634802e-01]
 [  1.93740856e-02   7.65220193e-03   2.38531725e-02   2.90952456e-03
   -4.30382963e-01   5.48058347e-03]
 [  1.41979449e-01   6.11143320e-02   1.67043402e-01   1.26494636e-01
   -3.89440590e-01  -2.49735998e-01]
 [ -4.22021007e-02  -2.07774840e-02  -4.89153648e-02  -4.20375760e-02
    9.32349816e-03   9.01488481e-02]
 [  1.95453023e-01   9.56225188e-02   2.31921649e-01   1.76559813e-01
   -2.67177481e-01  -4.19723236e-01]
 [  3.46601062e-02   1.57359455e-02   4.54843882e-02   3.16349183e-02
   -1.03527005e-02  -9.33809770e-02]
 [ -2.17183156e-02  -1.09060773e-02  -2.31646237e-02  -2.32297738e-02
    1.10983190e-02   4.23202531e-02]
 [  9.63833181e-02   3.64122287e-02   1.06917137e-01   7.85006330e-02
   -2.80438180e-01  -1.93959655e-01]
 [ -1.80363542e-01  -8.72776809e-02  -2.19214800e-01  -1.50251444e-01
    1.88840857e-01   3.52052721e-01]
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    5.69674607e-01   1.48699858e-01]
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   -9.27776982e-02  -2.59075310e-02]
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    4.73682701e-01   1.93728461e-01]
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   -3.56125201e-01  -2.74400945e-01]
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    4.76503448e-01   2.77258542e-01]
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    4.03450212e-01   4.60899312e-01]
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   -1.04334372e-01  -1.11692173e-01]
 [  4.67502291e-01   2.20635282e-01   5.29902837e-01   3.70025085e-01
   -8.61769895e-01  -9.63092364e-01]
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   -4.03748886e-01  -5.64571767e-01]
 [  5.40073539e-03   2.66950719e-03   6.08894664e-03   5.04725717e-03
   -1.50535092e-02  -1.10171146e-02]
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   -4.14150067e-01  -2.97245584e-01]
 [  5.81505666e-01   2.93633450e-01   6.82161404e-01   3.96989496e-01
   -1.00180315e+00  -1.22527120e+00]
 [  2.38709908e-01   1.19484712e-01   2.66858837e-01   2.31341997e-01
   -5.45086607e-01  -4.95805985e-01]
 [  2.38669637e-01   1.18910391e-01   2.84203358e-01   1.85448209e-01
   -3.06392822e-01  -4.08804617e-01]
 [  1.17228347e-01   4.68930732e-02   1.87760763e-01   1.05095089e-01
   -7.17109854e-01  -3.26981798e-01]
 [  1.46167969e-01   5.57467312e-02   1.57041451e-01   9.16008069e-02
   -5.91282423e-01  -2.09024861e-01]
 [ -5.60136965e-01  -2.39050089e-01  -6.44452706e-01  -5.14714201e-01
    1.68238317e+00   9.51776406e-01]
 [ -7.68021399e-01  -3.79341742e-01  -8.41836799e-01  -6.96856365e-01
    2.00790307e+00   1.55758872e+00]]
delta_weights_h_o = [[-0.58029772]
 [-0.18817388]
 [ 0.10361722]
 [ 0.42682966]
 [ 2.20370548]
 [ 0.67790739]]
self.weights_hidden_to_output = [[-0.97345688]
 [-0.47814507]
 [-1.11700719]
 [-0.90154615]
 [ 2.81458513]
 [ 2.00234959]]
self.weights_input_to_hidden = [[-0.14141727 -0.2841742  -0.29383461 -0.44257658  0.49816416  0.10499133]
 [-0.01392488  0.03406901 -0.07441941  0.13794089 -0.20743682 -0.02041754]
 [-0.10761857 -0.03160153 -0.00396544  0.29563385  0.76442397 -0.04726968]
 [-0.09147183 -0.13108273 -0.04433091  0.04688786 -0.31348827  0.08286121]
 [-0.02360268  0.03241404  0.10484577 -0.11566086  0.01007463  0.01532113]
 [ 0.15301339  0.24727005 -0.0586285  -0.02336925 -0.90811347 -0.06107409]
 [ 0.05673285  0.07068277  0.33395791 -0.02119102 -0.32476307 -0.04275786]
 [ 0.13343555 -0.16299554  0.0504108   0.10872193 -0.43311406 -0.17022825]
 [-0.10658543  0.0309345   0.15619408 -0.16964429 -0.32583051 -0.11543737]
 [-0.12442392 -0.04330046  0.07595773  0.00869878 -0.40306565  0.09743214]
 [ 0.19577994 -0.03164219 -0.01341046 -0.14291543 -0.34888379  0.01490588]
 [ 0.3148359   0.15898567  0.16949518 -0.17225609 -0.57718808 -0.28949247]
 [-0.0706043  -0.10018887 -0.12610967  0.054785   -0.08435157 -0.00283533]
 [ 0.12606935  0.03950005 -0.04817762 -0.10883907 -0.3191169  -0.20764922]
 [-0.00741746  0.06916656 -0.0569677   0.04046821 -0.50339922 -0.02561948]
 [-0.13205995  0.26765112  0.0508289  -0.19422087 -0.23687104  0.01567078]
 [ 0.03275985 -0.17785955 -0.01616046  0.08239367 -0.18144846 -0.16250385]
 [ 0.00953559 -0.23557324  0.04502501 -0.1981629  -0.32055943 -0.0482666 ]
 [ 0.18054437  0.19672061  0.12368767  0.03539776 -0.10916742 -0.06199551]
 [ 0.22921898 -0.05448266  0.10867494  0.09614762 -0.21268193 -0.05277403]
 [ 0.07544824 -0.05496014  0.05987081  0.10056187 -0.19509381  0.03148744]
 [-0.13661022 -0.06696288  0.01040253 -0.05364246 -0.02367349  0.01408995]
 [-0.08046378  0.12826613 -0.1176566   0.15853668 -0.01288993 -0.10328289]
 [ 0.21204624 -0.04816269 -0.06157742 -0.16496265 -0.24188757  0.12257775]
 [-0.01233823 -0.18929816  0.15225651 -0.21659907 -0.21311018  0.03299277]
 [ 0.18884033  0.08578052  0.33068236  0.31337879 -0.41772637 -0.56930751]
 [ 0.20078136 -0.09179077  0.47634479  0.2036254  -0.6721356  -0.59756395]
 [ 0.35181327  0.31094266  0.27102123  0.16685668 -0.71219946 -0.61010674]
 [ 0.19693638  0.10751915  0.43055045  0.36596047 -1.08264001 -0.41447668]
 [ 0.12071003  0.15656628  0.36386543  0.28048348 -0.96410695 -0.64580691]
 [ 0.45687176  0.25003302  0.11284404  0.36118821 -0.75333898 -0.51161217]
 [ 0.49958651  0.09079819  0.12315325 -0.13413621 -0.19512586 -0.51756241]
 [ 0.01830052  0.05434484  0.01651988 -0.22848718  0.35257721  0.0277058 ]
 [-0.48481448 -0.14533964 -0.26959786 -0.08911925  0.81378608  0.65619857]
 [ 0.07320755 -0.07858399 -0.25005838 -0.1207329   0.08691587  0.14931408]
 [-0.00496169  0.01611444 -0.18904006  0.19510947 -0.19288653  0.04236659]
 [ 0.02774002 -0.21997167  0.09662669 -0.0408074  -0.12894479  0.23252446]
 [-0.0764485   0.08723852 -0.37362494 -0.16010758  0.03407386  0.2709665 ]
 [ 0.15810189 -0.05088382 -0.05452848 -0.08097199  0.1514496   0.21272503]
 [-0.04003374  0.07278257 -0.02124721 -0.06315758  0.24259121 -0.036229  ]
 [-0.06011687 -0.15824394 -0.11558276 -0.16649892  0.00625928  0.00522479]
 [-0.04858215 -0.13841931 -0.21383331 -0.27019801  0.39966532  0.34757511]
 [-0.37197833 -0.31530799 -0.759798   -0.4779575   0.87845499  0.96603851]
 [-0.37828929 -0.1828159  -0.5184064  -0.35501084  0.88834223  0.77891435]
 [-0.15291081 -0.29484689 -0.00526153 -0.201627    0.65421069  0.34215738]
 [-0.13621415  0.1223647  -0.20163134 -0.11593517  0.22572715  0.01614819]
 [ 0.0374214  -0.20419352 -0.0607574  -0.16444699 -0.29191827  0.02396965]
 [ 0.04212038 -0.07478507  0.06627624  0.00230589 -0.37201988 -0.11157806]
 [ 0.253053    0.18712186  0.15978626  0.22086812 -0.43536199 -0.20584486]
 [ 0.02590349  0.13150391  0.05661967 -0.02538178 -0.3984324  -0.16137306]
 [ 0.06749261  0.16745762  0.08240145  0.19205045 -0.29254756 -0.09067987]
 [-0.02406008  0.00636265 -0.13737277  0.02665182 -0.30133466 -0.22943854]
 [ 0.11031753 -0.15370749  0.13668358 -0.01533858 -0.24414796 -0.19388501]
 [-0.21281338 -0.0439786   0.01477672  0.15930067 -0.38156299 -0.14091173]
 [ 0.20108756  0.13134146  0.26326301 -0.03159296 -0.2595091   0.09659919]
 [ 0.07618513 -0.12397075  0.16728836  0.1002376  -0.26093322  0.06181175]]
Progress: 4.8% ... Training loss: 0.269 ... Validation loss: 0.433hidden_inputs = [ 0.00443807  0.31984833  0.41371987 -0.12345418  0.11889708 -0.04490905]

plt.plot(losses['train'], label='Training loss')
plt.plot(losses['validation'], label='Validation loss')
plt.legend()
_ = plt.ylim()

Check out your predictions

Here, use the test data to view how well your network is modeling the data. If something is completely wrong here, make sure each step in your network is implemented correctly.

fig, ax = plt.subplots(figsize=(8,4))

mean, std = scaled_features['cnt']
predictions = network.run(test_features).T*std + mean
ax.plot(predictions[0], label='Prediction')
ax.plot((test_targets['cnt']*std + mean).values, label='Data')
ax.set_xlim(right=len(predictions))
ax.legend()

dates = pd.to_datetime(rides.ix[test_data.index]['dteday'])
dates = dates.apply(lambda d: d.strftime('%b %d'))
ax.set_xticks(np.arange(len(dates))[12::24])
_ = ax.set_xticklabels(dates[12::24], rotation=45)

OPTIONAL: Thinking about your results(this question will not be evaluated in the rubric).

Answer these questions about your results. How well does the model predict the data? Where does it fail? Why does it fail where it does?

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